Enterprises are adopting artificial intelligence faster than they are redesigning the workflows, workforce roles and governance structures needed to realize its full value, according to new research from Everest Group commissioned or released in partnership with Lean Solutions Group. The study, Designing the Human + AI Enterprise: A Transformation Agenda for Supply Chain-Intensive Industries, surveyed more than 200 U.S.-focused senior decision-makers across transportation, logistics and related industries. It found that while 69% of organizations have moved beyond isolated AI use cases, only 19% have significantly or extensively redesigned workflows for human–AI collaboration.

AI deployment is advancing faster than operational change

The findings point to a gap between implementing AI tools and restructuring how work gets done. According to the study, only 15% of surveyed organizations have made comparable changes to workforce roles, suggesting that many businesses are layering AI onto existing operating models rather than redesigning processes around the technology.

That distinction matters in supply chain-intensive industries, where decisions often involve incomplete information, time-sensitive exceptions and coordination across customers, carriers, warehouses and other stakeholders. Automating an individual task may improve speed, but broader operational gains can depend on how AI systems interact with employees, business rules and connected data.

The report also found that decision-making remains primarily human-led at 72% of organizations, while 60% rely primarily on people for exception handling. These figures suggest that human judgment continues to play a substantial role even as AI adoption expands.

For enterprise leaders, the challenge is therefore not just selecting AI platforms. It is determining which activities can be automated, where human review remains necessary, and who is accountable when an AI-assisted decision affects operations or customers.

Investment priorities reveal a readiness gap

The research highlights an imbalance between technology spending and organizational preparation. Some 67% of respondents prioritize AI platforms, and 66% prioritize data and integration. By comparison, 33% prioritize workforce upskilling, while just 17% prioritize governance and another 17% change management.

This investment pattern may create execution risks. AI tools depend on reliable data and integration, but successful deployment also requires employees to understand new workflows, managers to define decision rights, and organizations to establish oversight mechanisms.

Only 26% of respondents reported having formal structures for AI accountability. Without clear ownership, businesses may struggle to evaluate AI-generated recommendations, investigate errors and ensure that automated processes operate within approved boundaries.

The study also identifies a talent challenge specific to logistics and transportation: 58% of organizations in these sectors report talent shortages, compared with 35% in other surveyed industries. Human–AI collaboration could help employees focus on complex work, but realizing that benefit requires deliberate role design and training.

AI returns remain uneven despite high expectations

The study found that 84% of respondents report or expect meaningful AI value within two years. However, 30% said returns were below expectations, while 24% reported returns above expectations. The figures illustrate the difference between anticipated benefits and value already demonstrated.

External research points to a similar challenge. In October 2026, Gartner reported that only 13% of surveyed CIOs said their enterprises had achieved significant or transformational value from AI. Gartner also emphasized the importance of defining business value, establishing governance and setting criteria for scaling or stopping initiatives.

For supply chain operators, relevant measures can include delivery reliability, exception-resolution time, labor utilization, cost per shipment and customer satisfaction. These operational metrics give organizations a more concrete basis for assessing AI than adoption rates or the number of deployed tools alone.

Four stages for human–AI transformation

Everest Group’s report outlines a four-stage transformation path: Rewire, Replicate, Orchestrate and Adapt. The framework is intended to help organizations progress from individual AI applications toward coordinated execution across functions.

Lean Solutions Group connects these findings to its Experts in the Loop model, which combines AI-enabled technology with experienced professionals and redesigned workflows. Under this approach, AI handles suitable tasks within defined boundaries, while people provide oversight, resolve exceptions and retain responsibility for consequential decisions.

The announcement also describes a case study involving MOD Delivery Services, a final-mile logistics provider. According to Lean Solutions Group, the collaboration focused on standardizing processes, improving data visibility and supporting automation, while allowing logistics professionals to concentrate on exceptions, customer relationships and complex decisions. The announcement does not provide quantified results for the case study.

Looking ahead two to three years, respondents identified transportation planning and execution (53%), workforce scheduling and labor management (49%), and supply chain planning and coordination (48%) as leading opportunities for human–AI transformation.

The research was introduced alongside FreightWaves F3, held October 26–28 in Chattanooga, Tennessee. Its central message is that AI transformation requires more than deploying new tools: organizations must also redesign workflows, develop employee capabilities and establish clear accountability for results.

Market Landscape

The findings reflect a broader enterprise AI challenge: scaling adoption does not automatically produce measurable business value. Organizations need to connect AI investments to operating models, workforce capabilities, data infrastructure and governance.

Gartner’s October 2026 research similarly highlights operating-model redesign as a key factor in realizing AI value, rather than simply adding tools to existing processes.

In logistics, the stakes are particularly practical. AI can support planning, scheduling, forecasting and exception detection, but unreliable data, fragmented systems and unclear decision rights can limit its operational impact. Human oversight remains important where disruptions require contextual judgment or customer-specific decisions.

Strategic Outlook

For supply chain leaders, the report suggests evaluating AI transformation through three connected questions:

• Workflow redesign: Has the organization changed how work moves between AI systems, employees and business functions?

• Accountability: Are decision rights, escalation procedures and governance responsibilities clearly defined?

• Business value: Are AI initiatives improving measurable operational outcomes, not just adoption or task completion?

Lean Solutions Group’s Experts in the Loop approach is one model for combining automation with human expertise. Its effectiveness should ultimately be assessed through independently measurable outcomes, such as reduced processing times, improved delivery performance and lower operating costs.

The broader implication is that the next phase of enterprise AI competition may depend less on who deploys the most tools and more on who redesigns work most effectively around them.

Top Insights

• AI adoption is outpacing workflow transformation: 69% of surveyed organizations have moved beyond isolated use cases, but just 19% have significantly or extensively redesigned workflows.

• Workforce redesign remains limited: Only 15% report comparable changes to workforce roles, highlighting the organizational challenge of integrating AI into daily operations.

• AI returns remain inconsistent: While 84% report or expect meaningful value within two years, 30% report below-expectation returns and 24% report above-expectation returns.

• Governance and skills need more attention: Only 26% report formal AI accountability structures, while workforce upskilling ranks below technology and integration priorities.

• Logistics offers several transformation opportunities: Respondents identified transportation planning, workforce scheduling and supply chain coordination as leading areas for human–AI collaboration.

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Houston-based On-Target! Marketing & Advertising has been named a 2026 Winner of Distinction at the Better Business Bureau of Greater Houston’s 34th Annual Awards for Excellence. The recognition comes as the agency marks more than 25 years in business and positions itself as a full-service marketing and growth consultancy. Its service portfolio spans brand strategy, digital advertising, search engine optimization, AI visibility, CRM and sales enablement, reflecting how agencies are expanding beyond traditional advertising to connect marketing activity with measurable business outcomes.

BBB recognition highlights trust and business practices

On-Target! Marketing & Advertising was among 258 organizations recognized at the 2026 BBB Awards for Excellence, held September 30 before 960 attendees. The event, themed “Where Dreams Turn Into Wins!”, honored businesses and nonprofit organizations for their commitment to excellence in the Greater Houston marketplace.

For On-Target!, the award recognizes an agency whose leadership says trust, reliability and client outcomes have remained central to its work through decades of change in the marketing industry.

“Awards are nice, but what matters is what they represent,” said Tasha Steiner, COO of On-Target! Marketing & Advertising. She described the recognition as an acknowledgment of the agency’s efforts to deliver quality work, maintain its commitments and prioritize client success.

The BBB’s Awards for Excellence are designed to recognize organizations that demonstrate its Standards for Trust within their communities. The distinction is therefore relevant to the agency’s reputation and business practices, rather than a direct measurement of campaign performance or marketing return on investment.

From advertising agency to growth consultancy

Founded in Houston, On-Target! has evolved from a traditional advertising agency into a broader marketing and growth consultancy. Its current services include brand strategy, creative development, website development, SEO and AI visibility, digital advertising, content marketing, CRM, sales enablement, media and strategic consulting.

That range reflects a wider change in the agency sector. Businesses increasingly expect marketing partners to coordinate activity across brand development, digital channels, customer relationship management and sales processes, rather than manage each function independently.

For agencies, this creates an opportunity to connect marketing execution with commercial objectives. Website development, paid campaigns and content can help attract prospects, while CRM and sales enablement can support lead management and follow-through. The practical value depends on how well those services work together and whether the results can be measured against business goals.

On-Target! says its focus is helping businesses connect marketing with measurable growth. The announcement, however, does not disclose specific client results, revenue growth figures or campaign performance metrics associated with the agency’s work.

AI visibility adds another dimension to agency services

One of the services highlighted in the announcement is AI visibility, reflecting the growing interest in how brands appear across AI-powered search and answer platforms. As discovery expands beyond traditional search results, businesses are evaluating how clearly their expertise, services and brand information are represented online.

For marketing agencies, this creates new demands around technical SEO, useful content, structured information and brand credibility. However, AI visibility is an evolving discipline, and no agency can guarantee that a business will be cited or recommended by a particular AI platform. Its commercial value ultimately depends on whether improved discovery reaches relevant audiences and contributes to qualified leads or sales.

On-Target!’s combination of SEO, content marketing, digital advertising and CRM services positions the agency to address several stages of the customer journey. The announcement does not specify how its AI visibility offering is implemented or provide performance data demonstrating its impact.

A long-term emphasis on client relationships

The agency’s leadership frames the BBB recognition as an affirmation of values that have remained important throughout its 25-plus years in business. Steiner said marketing technology has changed substantially, but clients continue to expect clear communication, honest advice and dependable support when projects become challenging.

That perspective highlights a continuing challenge for marketing consultancies: adopting new technologies while maintaining the relationships that underpin long-term client work. AI, automation and evolving digital channels can change how campaigns are executed, but they do not remove the need for accountability, sound judgment and an understanding of client priorities.

For On-Target!, the award provides external recognition from a regional business organization. The next measure of its positioning will be how effectively it continues to translate its broad service portfolio and client-focused approach into outcomes businesses can evaluate.

Market Landscape

Marketing agencies are increasingly expected to combine creative strategy with digital execution, lead generation and performance measurement. As businesses manage more channels and customer data, integrated services can help connect brand awareness with lead management and sales activity.

AI visibility is an emerging addition to this mix. While traditional SEO remains important, brands are also exploring how their information is surfaced in AI-generated responses. The strongest foundations remain useful content, technically accessible websites, credible sources and accurate business information.

The BBB recognition offers a reputation signal for On-Target! within the Greater Houston business community. It should not be interpreted as an independent certification of marketing effectiveness or proof that the agency outperforms competitors.

Strategic Outlook

On-Target!’s recognition underscores the role trust and reputation can play in a competitive services market. Its evolution from a traditional advertising agency to a broader growth consultancy reflects changing client expectations for connected marketing services.

For agencies, the opportunity is to combine emerging capabilities such as AI visibility with established strengths in strategy, creative work and client relationships. The challenge is to demonstrate results through transparent reporting, qualified lead generation, conversion performance and long-term client outcomes.

The award marks a milestone for On-Target!, while its longer-term business value will depend on the agency’s continued ability to deliver on the principles its leadership emphasizes: quality, accountability and client success.

Top Insights

• On-Target! Marketing & Advertising received a 2026 BBB Winner of Distinction award, joining 258 organizations recognized at the Greater Houston Awards for Excellence.

• The Houston-based agency has operated for more than 25 years, evolving from traditional advertising into a broader marketing and growth consultancy.

• Its services span SEO, AI visibility, digital advertising, content and CRM, reflecting demand for connected marketing and sales capabilities.

• The recognition emphasizes business trust and organizational standards, rather than independently verifying campaign performance, client growth or marketing return on investment.

• On-Target! leadership says client relationships remain central, even as marketing evolves through search, automation, social media and artificial intelligence.

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Ballantine Digital and manufacturing support organization MANTEC are hosting a free webinar on November 11, 2026, to help manufacturers adapt their digital marketing strategies to AI-powered search. Titled Winning AI Search: How Manufacturers Can Get Cited, Mentioned, and Recommended, the virtual session will be presented by Ballantine Digital Managing Partner Ryan Coté. The event will cover website structure, answer-ready content, structured data and external brand signals as manufacturers look for ways to remain discoverable when industrial buyers use AI tools to research suppliers.

AI search becomes another discovery channel for manufacturers

Manufacturers have traditionally relied on search engine rankings, industry directories, trade publications, referrals and sales relationships to attract prospective buyers. AI-powered search tools are adding another route through which purchasing teams can research suppliers, compare capabilities and identify potential partners.

Ballantine Digital and MANTEC’s upcoming webinar will focus on how industrial businesses can improve their chances of appearing in AI-generated answers. The session is scheduled for Wednesday, November 11, from 11 a.m. to noon Eastern time. Registration is free, and the event will take place online.

The session, led by Coté, will examine Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO). These terms describe practices intended to make information easier for AI-driven search experiences to find, interpret and potentially cite. They overlap with established SEO practices, including accessible website architecture, useful content, clear business information and credible external references.

For manufacturers, the issue is more specific than simply attracting website traffic. Industrial buyers may be searching for a supplier with a particular production capability, material specialization, certification, geographic footprint or ability to meet technical requirements. A company’s online presence needs to communicate those details clearly enough for both people and search systems to understand them.

What manufacturers will learn

The webinar will cover six areas of AI search optimization:

• Website structure and technical optimization: Making important company and capability information accessible to search engines and other discovery systems.

• Answer-ready content: Creating pages that directly address common customer and procurement questions.

• Topical authority: Demonstrating industry expertise through useful, technically accurate content.

• Schema markup and structured data: Providing machine-readable context about products, services and organizations.

• Reviews, backlinks and brand mentions: Building credible signals beyond a company’s own website.

• AI visibility assessment: Reviewing how a manufacturer currently appears in AI-powered search experiences and prioritizing improvements.

These topics reflect a practical challenge for industrial marketers: ensuring that a website explains what a company makes, which markets it serves, what differentiates its capabilities and how buyers can take the next step.

Why industrial businesses need a different AI search strategy

Manufacturing websites often serve audiences with highly specific research needs. A procurement manager evaluating a component supplier may need technical specifications, production capabilities, certifications, industry experience and evidence of quality—not just a general company overview.

That makes subject-matter expertise and detailed product information especially important. Manufacturers can strengthen their digital presence by publishing useful technical resources, answering recurring buyer questions and connecting capability pages with relevant case studies and industry applications.

There are limits to what optimization can achieve, however. Google says its AI search features rely on existing Search systems and established SEO practices; there are no additional requirements that guarantee inclusion in AI Overviews or AI Mode. The company recommends making content crawlable, useful, reliable and consistent with structured data where it is used.

The webinar offers manufacturers a framework for evaluating these fundamentals and identifying gaps in their current search strategy. Its practical value will depend on how attendees translate the guidance into improvements they can measure, such as qualified organic traffic, relevant inquiries and sales opportunities.

Market Landscape

AI search optimization is emerging as an extension of established SEO rather than a complete replacement for it. Manufacturers still need technically accessible websites, clear service and product information, credible references and content that answers buyers’ questions.

Google’s guidance is particularly relevant to claims about GEO and AEO. It says there is no special schema markup or separate optimization requirement for appearing in its AI search experiences. Structured data can support broader search eligibility when implemented correctly, but it does not guarantee citations or recommendations.

For industrial businesses, the opportunity lies in making specialist knowledge easier to discover and understand. The challenge is doing so without replacing technical depth with generic content designed merely to attract AI attention.

Strategic Outlook

The November webinar reflects growing interest in how manufacturers can adapt digital marketing to changing buyer research habits. For companies with complex products and long sales cycles, AI search visibility may become one component of a wider strategy that includes technical SEO, content marketing, industry reputation and sales enablement.

Manufacturers should establish a baseline before making major changes. Useful measures include relevant search traffic, visibility for high-intent technical queries, referral visits from AI platforms where measurable, qualified inquiries and opportunities influenced by organic discovery.

The key is to distinguish visibility from commercial impact. Being cited by an AI system may help a company enter a buyer’s consideration set, but it does not automatically lead to a qualified opportunity. The strongest strategy connects discoverability with credible evidence of manufacturing expertise and a clear path to contacting the business.

Top Insights

• Ballantine Digital and MANTEC will host a free AI search webinar on November 11, 2026, aimed at manufacturers seeking to improve their visibility across AI-powered discovery platforms.

• Ryan Coté will cover GEO and AEO fundamentals, including website structure, answer-ready content, topical authority, structured data, reviews and external brand mentions.

• Manufacturers need to communicate technical capabilities clearly, including product specifications, certifications, production expertise and industry applications that influence supplier selection.

• Google says established SEO best practices remain relevant to AI search, and no special optimization or schema markup guarantees inclusion in AI-generated search experiences.

   

• Measuring business outcomes remains essential, with qualified inquiries, sales opportunities and relevant organic traffic offering more actionable evidence than AI mentions alone.

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CMO Huddles has released a 51-page playbook designed to help B2B chief marketing officers prepare their organizations for AI-driven change. Developed by its Future of Marketing Organizations (FOMO) Task Force, The AI-Ready Marketing Organization: A Strategy-First Playbook for B2B CMOs examines how strategy, workflows, shared intelligence, governance and human judgment should shape AI adoption before companies restructure marketing teams. The report’s central message is that AI readiness is an organizational design challenge—not simply a technology rollout or a mandate to produce more content with fewer resources.

A strategy-first approach to AI adoption

The free playbook launched at CMO Huddles’ CMO Super Huddle, where approximately 90 marketing leaders gathered to discuss AI adoption, organizational change and business growth. Rather than prescribing a single structure for every company, the report provides a framework for assessing current capabilities and deciding how marketing work should evolve as AI changes execution.

CMO Huddles founder Drew Neisser argues that marketing leaders are positioned to lead this transition because they understand customers, work across sales and product teams, and have experience managing organizational change. The challenge is translating that position into a practical strategy that connects AI investments with business objectives while maintaining employee trust.

That distinction matters for B2B marketing teams adopting generative AI and AI agents. Tools can accelerate content production, research, analysis and other workflows, but productivity gains do not automatically produce stronger pipeline performance, customer engagement or revenue. Leaders must first define the outcomes they want to improve, identify how work needs to change and determine where human oversight remains essential.

Three models for organizing AI-ready marketing teams

The report outlines three organizational models, each designed for different operational needs.

• Optimizer: Improves existing functional teams and their workflows without fundamentally changing the organization’s structure.

• Integrator: Consolidates duplicated capabilities and connects work across functions to improve coordination and efficiency.

• Outcomer: Gives cross-functional teams responsibility for business outcomes, supported by shared capabilities and clear decision-making authority.

The models are presented as choices rather than compulsory stages. A company might strengthen its existing teams through an Optimizer approach, centralize selected capabilities through an Integrator model, or organize work around shared outcomes through an Outcomer structure. Different approaches may coexist within one organization.

The choice depends on business strategy, company size, technical capabilities and readiness for change. For example, a team struggling with inconsistent processes may benefit from improving its current workflows before centralizing functions. A larger organization facing duplicated technology and fragmented customer data may need stronger shared capabilities. Companies seeking tighter alignment between marketing activity and revenue outcomes may consider cross-functional teams with explicit accountability.

The playbook’s emphasis on context is significant because organizational redesign can create disruption when roles, decision rights and workflows are changed before the underlying business problem is understood.

Governance, shared intelligence and the economics of AI

Beyond organizational models, the playbook examines the capabilities needed to make AI adoption sustainable. These include managing shared knowledge, establishing governance, deciding how AI agents should operate and determining how to reinvest the time freed by automation.

Shared intelligence is particularly important for B2B marketing organizations. If customer insights, campaign learnings and operational knowledge remain fragmented across teams, AI tools may accelerate individual tasks without improving coordination across the broader marketing function. Common data foundations, clear ownership and agreed processes can help teams apply AI more consistently.

Human judgment remains another central consideration. As AI increases the speed and volume of content and campaign production, organizations need explicit standards for quality, review, brand alignment and accountability. Faster production is valuable only when it supports the intended business outcome.

The report also calls attention to the economics of transformation. Leaders must assess not just software costs, but also integration, training, oversight and the resources required to maintain AI-enabled workflows. They must then decide whether recovered capacity should be directed toward pipeline growth, customer experience, strategic planning or other priorities.

The playbook includes seven practical actions, decision worksheets and an AI-ready marketing scorecard. CMO Huddles says the report reflects contributions from its FOMO Task Force, with CMOs Heidi Bullock and Kathie Johnson presenting highlights at the Super Huddle.

Market Landscape

The playbook arrives as marketing leaders face a widening gap between AI investment and organizational readiness. Gartner’s 2026 CMO Spend Survey found that marketing organizations allocate an average of 15.3% of their budgets to AI initiatives, but only 30% of respondents said their organizations had mature or fully developed AI readiness capabilities.

That gap helps explain why organizational design is becoming a priority alongside tool selection. Marketing teams may already use AI for content creation, research and campaign execution, yet still lack the governance, shared data, workflow integration and decision-making structures needed to scale those applications.

Gartner also reported in May 2026 that marketing leaders expect AI-driven automation to increase from 16% of marketing work in 2026 to 36% by 2028. These are expectations reported by surveyed CMOs, not a forecast that every marketing organization will achieve that level of automation.

Against this backdrop, CMO Huddles’ three models offer a framework for evaluating how work should be organized. Their value lies in helping leaders connect operating-model decisions to business needs, rather than assuming that centralization or cross-functional restructuring is always the right answer.

Strategic Outlook

The playbook’s strongest recommendation is to begin with business outcomes and workflow redesign before changing organizational charts. For CMOs, this means establishing a baseline, selecting a measurable priority and identifying where AI can improve the work. Structural changes should follow evidence about what the organization needs to deliver.

The next challenge is accountability. Marketing leaders must determine who owns AI-enabled workflows, which decisions require human review, how shared capabilities are funded and how productivity gains will be reinvested. These choices also require coordination with sales, customer success, product, IT and Finance.

CMO Huddles’ framework does not promise a universal model for AI transformation. Instead, it encourages leaders to select and combine approaches according to their organization’s maturity, strategy and resources. As AI adoption expands, that emphasis on deliberate design could prove more useful than simply adding new tools to existing processes.

Top Insights

• CMO Huddles released a 51-page AI-ready marketing playbook to help B2B CMOs align AI adoption with business strategy, organizational design and measurable outcomes.

• The report outlines three organizational models—Optimizer, Integrator and Outcomer, allowing companies to choose structures based on their goals, capabilities and readiness for change.

• Gartner found only 30% of surveyed marketing organizations had mature or fully developed AI readiness capabilities, highlighting the gap between investment and organizational preparedness.

   

• The playbook prioritizes workflow redesign, governance and human judgment, urging leaders to evaluate how work should change before making decisions about roles and reporting structures.

• Cross-functional coordination is central to the framework, with marketing expected to align AI initiatives with sales, customer success, product, IT and Finance.

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As enterprise organizations invest in artificial intelligence, turning platform capabilities into measurable business outcomes is becoming a central challenge for customer success teams. Jessica Beam, Manager of Customer Success at Uniphore, approaches that challenge through strategic partnership, active listening and accountability. Profiled by Influential Women, Beam represents a customer success model that connects AI adoption with customer retention, cross-functional collaboration and long-term value creation—while drawing on her experience in marketing technology and her commitment to community service.

Connecting enterprise AI with customer outcomes

Jessica Beam works with enterprise customers at Uniphore, helping organizations adopt AI-powered solutions, increase platform utilization and identify opportunities for long-term growth. With more than seven years of experience spanning customer success and digital marketing, she operates across product, marketing, technical and executive teams to align customer goals with business priorities.

Her approach reflects a broader shift in customer success management. Rather than concentrating primarily on resolving problems after they arise, customer success teams increasingly work to support adoption, demonstrate value and identify risks to retention before they become larger issues. In enterprise AI, this requires more than explaining product features: teams must understand the customer’s operational needs and connect technology usage to outcomes that matter to the organization.

Beam emphasizes consultation before recommendation. By listening to stakeholders, clarifying objectives and following through on agreed actions, she aims to build relationships based on trust rather than short-term transactions. Her philosophy centers on empathy, transparency and accountability, with success measured by customer outcomes instead of activity alone.

From marketing technology to strategic partnership

Beam began her career in retail and other customer-facing roles, developing interpersonal skills that later shaped her work in technology. While earning a Bachelor of Science in Digital Marketing from Southern New Hampshire University, she moved into the vendor side of the industry, including a role at marketing technology company Bluecore.

There, she supported enterprise customers and contributed to retention and revenue growth through structured success planning and campaign optimization, according to her profile. She also holds an Associate of Applied Science in Fashion Merchandising Management from the Fashion Institute of Technology.

This combination of marketing and customer-facing experience gives her a perspective on how organizations connect technology investments with business performance. In software businesses, adoption alone does not necessarily demonstrate value. Customers need to see how a platform supports their goals, whether those involve improving workflows, increasing efficiency, strengthening customer relationships or generating measurable returns.

Beam’s emphasis on stakeholder alignment is especially relevant to enterprise deployments, where purchasing decisions, technical implementation and day-to-day usage may involve different teams. Customer success professionals must help those groups agree on priorities and maintain a shared understanding of progress.

Why listening matters in AI-driven customer success

Beam credits a TED Talk about listening to understand, rather than listening simply to respond, as influential career advice. The principle informs how she approaches client conversations: uncovering the underlying need before proposing a solution.

As AI tools become more capable, this human-centered skill remains important. Technology can assist with information retrieval, analysis and workflow automation, but customer relationships also depend on context, communication and judgment. A customer may need help defining the problem before a technical solution can be evaluated effectively.

Beam has continued to develop her skills through additional education and training, including data analytics, General Assembly coursework, Google Prompting Essentials and AI Fluency Framework and Foundations training. She has also completed courses covering AI-assisted analysis, presentation development and Claude Cowork. These credentials reflect an ongoing commitment to learning as digital tools and customer expectations evolve.

Customer success is becoming more strategic

Beam sees the profession moving beyond reactive support toward closer collaboration with sales, product and executive leadership. One of its key challenges is demonstrating value across complex stakeholder environments, particularly as customers expect technology investments to deliver clear results.

For enterprise AI providers, customer success can help bridge the gap between a platform’s technical capabilities and its practical business applications. Teams must understand how customers use the technology, identify barriers to adoption and communicate progress in terms that business leaders can evaluate.

That work also creates opportunities to identify expansion needs and strengthen customer relationships. However, retention and growth depend on multiple factors, including product performance, implementation quality, customer expectations and the ability to demonstrate sustained value. Relationship management is an important part of that equation, not a substitute for measurable outcomes.

Beam encourages women entering customer success, sales and marketing to build confidence through experience rather than wait for perfection. She also highlights emotional intelligence, body-language awareness, comfort with difficult conversations and a willingness to seek honest feedback as valuable professional skills.

Wellness and community service beyond the workplace

Outside her role at Uniphore, Beam is a certified Pilates instructor and founder of Bodied by Beam, a wellness initiative focused on balance, movement and physical strength. She hopes to open a Pilates studio that combines movement, education and holistic well-being.

She also volunteers with Bottomless Closet, an organization that supports economically disadvantaged women returning to the workforce through career development and professional branding. The work connects with her interest in helping women build confidence and access new opportunities.

Beam’s professional and personal pursuits share a common theme: supporting people through listening, education and practical guidance. As enterprise organizations continue adopting AI, her approach underscores why customer success remains a relationship-driven discipline, even when the products involved are increasingly automated.

For technology companies, the challenge is to combine AI capabilities with human understanding, cross-functional execution and clear accountability. Beam’s career offers one example of how those principles can shape customer relationships in the evolving enterprise software market.

Market Landscape

Enterprise AI adoption puts greater emphasis on the work that happens after a software purchase. Organizations must integrate tools into existing processes, encourage employees to use them appropriately and determine whether deployments are producing meaningful results.

Customer success teams are well positioned to support that work because they connect customer feedback with product, technical and commercial teams. In subscription software businesses, they can also help identify adoption risks and communicate opportunities for deeper product use.

The role is evolving, but the fundamentals remain consistent: understand customer objectives, establish measures of success, monitor progress and address problems before they undermine the relationship. AI may help teams analyze usage patterns or streamline routine tasks, while customer-facing professionals remain responsible for interpreting context and coordinating action.

Strategic Outlook

As AI becomes more embedded in enterprise software, customer success professionals will need to combine technical fluency with business judgment and interpersonal skills. They must understand what AI-powered platforms can do while helping customers set realistic expectations and evaluate results.

Beam’s emphasis on empathy, continuous learning and accountability highlights the human side of that transition. For enterprise technology companies, effective customer success is not simply about increasing usage; it is about helping customers achieve outcomes they can recognize, measure and sustain.

Top Insights

• Jessica Beam leads customer success at Uniphore, helping enterprise clients adopt AI-powered solutions, improve platform utilization and identify opportunities for long-term account growth.

• Her approach emphasizes empathy, transparency and accountability, positioning active listening and clear communication as essential skills in complex enterprise customer relationships.

• Beam’s background includes marketing technology experience at Bluecore, where she supported enterprise customers and contributed to retention and revenue growth initiatives.

• Enterprise customer success is shifting toward strategic partnership, requiring closer collaboration across product, sales, technical and executive teams to demonstrate business value.

• Through Bodied by Beam and Bottomless Closet volunteering, Beam extends her focus on confidence, wellness and professional development beyond her corporate technology role.

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Beacon Media + Marketing has published its first Beacon Signal Report: The 2026 State of Mental Health Marketing, examining how mental and behavioral health practices attract patients, measure marketing performance and navigate advertising compliance. Combining survey responses from practice owners and clinical leaders with six months of agency performance data, the report identifies a central challenge: helping prospective patients choose a provider after discovering one online. Its findings highlight persistent gaps in lead tracking, healthcare advertising policy awareness and the use of clinically informed content across digital channels.

Mental health marketing shifts from discovery to patient conversion

The report draws on a survey conducted from July 17 to August 2, 2026, alongside internal performance data from 29 mental and behavioral health clients covering January 1 through July 31, 2026. Survey respondents included practice owners, clinical directors and marketing leads from organizations ranging from solo practices to multi-location franchises and treatment centers.

According to Beacon, the findings suggest that visibility alone is no longer enough to drive patient acquisition. Prospective patients want practical answers about insurance acceptance, treatment specialties, appointment availability and provider credibility before contacting a practice.

That changes the role of healthcare marketing. Search rankings, social media reach and directory listings can introduce a provider to potential patients, but conversion depends on whether the practice communicates relevant information clearly and makes the next step straightforward. For marketers, the challenge is connecting discovery with the practical requirements that influence a patient’s decision to seek care.

The report also argues that patient discovery increasingly spans multiple channels, including search engines, social platforms, online directories, reviews, community platforms and AI-powered search experiences. Practices therefore need to understand how these channels work together rather than evaluate each in isolation.

Specific content and clinical expertise can build trust

Beacon’s performance data suggests that content addressing a specific patient question can outperform generic social posts. One client’s post explaining that ADHD cannot be diagnosed through a single test generated nearly 72,000 views, according to the agency. Provider introductions and clinician perspectives also performed well in its sample.

The result illustrates a potential advantage for healthcare organizations competing in an environment increasingly filled with automatically generated content: direct clinical expertise can provide context, nuance and credibility that generic informational posts may lack.

However, reach is not the same as patient acquisition. The announcement does not establish how many viewers became qualified leads or patients, nor does it provide a comparative benchmark for other content formats. Practices should assess content through a combination of engagement, relevant website visits, inquiries and completed appointments, while protecting patient privacy.

AI-powered search creates another reason to make content clear and specific. When people ask conversational tools about symptoms, treatment options or local providers, practices benefit from having accurate service descriptions and useful information available online. Inclusion in AI-generated answers, however, is not guaranteed by any particular content or optimization tactic.

Lead attribution and advertising compliance remain obstacles

The report identifies marketing measurement as the leading challenge among surveyed practices. Only 32% of respondents said they track leads in a dedicated system, according to Beacon. Without a reliable way to connect advertising spend to inquiries and completed appointments, practices may struggle to identify which campaigns generate patients rather than superficial engagement.

Beacon’s Denali Taylor points to customer relationship management (CRM) systems and offline conversion tracking as ways to connect digital campaigns with outcomes that occur beyond a website. Implementing these systems requires more than installing analytics tools: practices need consistent lead definitions, reliable intake records, appropriate attribution methods and processes for handling sensitive information.

Compliance presents a separate challenge. Beacon reports that 58% of respondents were unfamiliar with LegitScript or Google’s healthcare and addiction advertising policies. Google restricts certain healthcare advertising categories and requires certification for some services and markets. Requirements vary by service and location, so practices need to confirm which rules apply before launching campaigns.

Healthcare analytics also demands careful data governance. Practices should assess whether tracking technologies and marketing vendors handle protected health information appropriately and whether their arrangements meet applicable legal requirements. The U.S. Department of Health and Human Services outlines relevant HIPAA obligations, while noting that a portion of its tracking-technology guidance was vacated by a federal court in 2024.

Beacon plans to publish the Signal Report every six months, giving practices a recurring view of how marketing challenges and performance patterns evolve. The report is available free through the agency’s website.

Market Landscape

Mental and behavioral health providers operate in a marketing environment where patient discovery, trust and access are closely connected. Search engines, social networks, directories and AI tools offer different paths to discovery, but providers must still explain their services and make it easy for prospective patients to take the next step.

Beacon’s report contributes a useful practitioner perspective by pairing survey responses with performance data from 29 clients. However, the sample reflects the agency’s own client roster and survey respondents, rather than a representative census of the entire mental healthcare sector. Its findings should therefore be treated as directional insights, not universal industry benchmarks.

The compliance findings are particularly relevant for practices promoting addiction treatment or other regulated healthcare services. Google’s policies distinguish between service categories and target markets, with certification requirements applying to certain ads.

Strategic Outlook

The report’s central implication is that mental health marketing needs to connect visibility with access, trust and measurable patient outcomes. Practices can use clinically informed content to answer common questions, improve service pages with clear insurance and appointment information, and assess whether campaigns produce qualified inquiries.

The next step is better attribution. CRM adoption and offline conversion tracking can help practices understand which channels contribute to appointments, but implementation should account for privacy, data minimization and vendor access. Marketing teams should also distinguish between metrics such as views and clicks and outcomes such as qualified leads and completed visits.

For Beacon, the planned six-month reporting cadence could help identify changes in channel performance and practice needs over time. Its longer-term value will depend on transparent methodology, comparable reporting periods and evidence showing whether recommended approaches improve measurable outcomes.

Top Insights

• Beacon’s 2026 Signal Report examines mental health marketing using survey responses and six months of paid advertising, social media and content data from 29 clients.

• Lead tracking is the leading challenge identified by respondents, with only 32% reporting that they use a dedicated system to track leads.

• Healthcare advertising compliance remains a knowledge gap, as 58% of surveyed respondents said they were unfamiliar with LegitScript or Google healthcare and addiction advertising policies.

• Specific, clinically informed content can attract attention, with Beacon reporting nearly 72,000 views for one client’s post explaining ADHD diagnosis.

• The report emphasizes patient conversion over visibility alone, highlighting insurance information, treatment fit, appointment access and trust as factors in the decision to seek care.

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Real estate brokerage 1 Percent Lists Mid-Atlantic has partnered with digital marketing agency One Click SEO to strengthen its visibility in Google Maps results and AI-generated search answers. The strategy combines local search optimization, structured entity data and Generative Engine Optimization (GEO), targeting homeowners across the greater Baltimore region. The announcement reflects a wider shift in local marketing: businesses are increasingly looking beyond traditional search rankings to how search platforms identify, describe and recommend local service providers.

Real estate brokerage targets Google Maps and AI search

1 Percent Lists Mid-Atlantic, owned and operated by Maryland real estate professional Anthony “Tony” Fulco, offers full-service real estate representation with a 1% listing fee. The brokerage says its franchise network has saved clients more than $65 million in traditional commissions.

Under the new partnership, New Orleans-based One Click SEO will apply local SEO and GEO strategies intended to increase the brokerage’s visibility across Google’s Map Pack and conversational AI search experiences. The plan includes local entity mapping for individual service areas, structured data, review-generation programs and what the agency describes as citation architecture.

For a geographically focused business, these tactics address different but related discovery mechanisms. Local SEO helps search engines connect a business with relevant queries and locations. Structured data can clarify details about an organization and its services, while consistent business information and credible third-party references can help establish its online identity. GEO aims to improve how a business is represented in AI-generated answers, although no single optimization technique guarantees inclusion in those responses.

The brokerage serves communities across Harford County, Baltimore County and Anne Arundel County, including Bel Air, Aberdeen, Havre de Grace, Pasadena and Severna Park. The partnership is intended to tailor local search signals to these individual markets rather than rely solely on broad regional targeting.

Why AI search is becoming part of local marketing

Consumers looking for a real estate agent may encounter businesses through traditional search listings, map results, reviews, AI summaries or conversational assistants. That creates a more fragmented discovery journey for local service providers, which must maintain accurate business information and demonstrate relevance across multiple channels.

Google’s local results are influenced by factors including relevance, distance and prominence. Businesses can improve their profiles and the quality of their local information, but they cannot directly control a searcher’s location or guarantee a particular ranking. Similarly, visibility in AI-generated answers depends on the platform, query, available information and its retrieval systems.

One Click SEO says it will use proprietary tools and local entity engineering to strengthen the brokerage’s digital footprint. The company also plans to use systematic review-velocity programs. The announcement, however, does not provide baseline rankings, a measurement period, promised ranking targets or independent results demonstrating the effectiveness of this particular engagement.

Commission transparency creates a competitive opening

The partnership also comes as real estate brokerages compete to communicate their pricing models after changes associated with the National Association of Realtors’ 2024 settlement. The settlement introduced practice changes, effective August 17, 2024, including written buyer agreements before home tours for covered MLS participants and restrictions on communicating offers of buyer-broker compensation through MLS platforms. It did not eliminate real estate commissions or establish a universal commission rate; broker compensation remains negotiable.

Against that backdrop, a 1% listing-fee model gives the brokerage a distinct proposition to communicate online. Search visibility could help consumers discover that alternative, but the agency’s technical work will need to be matched by clear service descriptions, transparent pricing information and credible customer reviews.

The distinction matters because a high search position does not automatically translate into qualified leads or closed transactions. For a real estate business, the meaningful measures are likely to include calls, consultation requests, qualified leads, signed listings and acquisition costs—not simply rankings or AI citations.

Market Landscape

Local search remains important for service businesses because results are influenced by the relationship between a query, a business’s location and its prominence. Google identifies relevance, distance and prominence as the main factors behind local results, while recommending accurate Business Profile information and active review management. It also says businesses cannot request or pay for better organic local rankings.

Google Business Profile Help

AI search adds another layer, but its mechanics should not be confused with a separate guaranteed ranking system. Google says its AI Overviews and AI Mode use the same foundational SEO principles as conventional Search; there are no additional technical requirements that guarantee inclusion. Pages must still be eligible for indexing and comply with Search policies.

Google for Developers

For real estate marketers, this means local SEO and GEO should complement—not replace—strong websites, accurate business profiles, useful location-specific content, consistent business details and reputable third-party references. One Click SEO’s approach may help organize those elements, but its specific claims about dominating Google Maps or AI answers remain objectives rather than independently demonstrated outcomes.

Strategic Outlook

The partnership illustrates how local businesses are adapting their customer-acquisition strategies to a search environment that includes map listings and AI-generated answers. The immediate opportunity is to make the brokerage’s locations, services and pricing proposition easier for prospective clients to discover and understand.

The harder task is proving commercial impact. A robust measurement plan would track local visibility by market, profile interactions, referral traffic, inbound calls, qualified leads and conversion rates. AI-search monitoring should record when the brokerage is cited or recommended across repeated, relevant queries, while accounting for variation between platforms and individual searches.

For publishers and marketers, the key lesson is that GEO should be treated as an evolving optimization practice, not a guaranteed route to AI recommendations. A 2026 survey of GEO research highlights limitations in the evidence for stable, long-term effects on organic discovery and downstream behavior.

For 1 Percent Lists Mid-Atlantic, success will ultimately depend on whether better discovery helps homeowners find a suitable agent and understand the value of its fee structure. Search visibility is the mechanism; qualified business outcomes are the test.

Top Insights

• 1 Percent Lists Mid-Atlantic has hired One Click SEO to improve local search visibility across Google Maps and AI-driven search experiences in Maryland.

• The strategy combines local SEO, structured entity data and GEO, with separate local optimization planned for communities throughout the greater Baltimore service area.

• The brokerage’s 1% listing-fee model provides a clear consumer proposition, but search optimization alone cannot establish whether that model will win more listings.

• Google’s local rankings depend on relevance, distance and prominence, making accurate business information and credible reviews important alongside technical optimization.

   

• The partnership has not disclosed measured performance gains or guaranteed ranking outcomes, so lead quality, conversions and customer acquisition costs will be important evaluation metrics.

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Newborn Town’s social gaming platform TopTop is bringing AI-generated 3D characters into multiplayer gameplay through Slap Showdown, a mini-game developed with world-model company Viggle. The game lets users turn personal photos into playable 3D characters in around 30 seconds, combining avatar customization with physics-based interaction. The launch offers an early example of how world models could move beyond AI-generated media into interactive consumer applications, while raising broader questions about engagement, scalability and the role of personalized content in social gaming.

AI-generated characters become part of the gameplay

Launched in September, Slap Showdown uses Viggle’s Joint Space-Time (JST) world model to convert uploaded photos into customized 3D characters. Players can create characters inspired by styles ranging from anime and cyberpunk to LEGO-like figures, then use them in multiplayer battles.

The distinction from conventional avatar customization is that these characters are not simply visual assets. Players interact through controls such as tapping, dragging and pressing and holding, while characters respond with physics-based movements. AI-generated content becomes part of the game mechanics rather than remaining a standalone image or video.

TopTop says the game has gained traction in Japan, among Spanish-speaking users in North America, and across the Middle East. According to the company, Slap Showdown recorded a 97% match completion rate in its first month, while its game-start rate exceeded the platform-wide average. These are company-reported figures; the announcement does not provide a comparison period, sample size or independent validation.

The reported activity of individual players also points to concentrated engagement. One player in Japan completed 1,041 matches over 22 days, while another in Eastern Europe completed 735 matches in 11 days. These examples illustrate heavy use among some players, but do not establish average engagement across the wider user base.

Why world models matter for social gaming

For user-generated-content platforms, personalized characters can give players more ways to express themselves, participate with friends and share in-game moments. That may create additional reasons to start a game and return to the platform, although sustained retention and monetization gains would need to be demonstrated through longer-term data.

World models are relevant because they aim to represent how objects and environments behave, rather than generating only plausible pixels. In Slap Showdown, that approach supports characters that move within an interactive game. If the technology becomes practical at scale, developers could extend customization to environments, objects and more dynamic gameplay.

TopTop says it is exploring AI-generated environments and new mechanics for existing games. Those plans suggest a broader product strategy: using AI to refresh its game catalog and deepen the social experience, rather than treating AI as a single feature launch.

Viggle’s JST-2 points toward a broader AI infrastructure role

Viggle positions its Joint Space-Time technology as a foundation for generating 3D characters, motion and scenes. The company first drew attention with Meme Maker, an AI video tool that animates static characters using specified movements. In August 2024, it raised $19 million in a Series A funding round led by Andreessen Horowitz.

On October 19, Viggle announced the full launch of JST-2, a physics-native world model designed to represent 3D structures and their dynamics. According to the company’s description, its representation uses units with spatial positions and physical attributes such as material, color and mass, alongside information about motion and responses to forces.

Viggle says JST-2 can generate a 3D scene in seconds for less than one U.S. cent in inference costs. It also says generated content can be rendered locally without repeatedly invoking the foundation model for every frame. These are vendor-reported performance and cost claims, and the announcement does not specify standardized benchmarks or the hardware and workload assumptions behind them.

If those economics hold across production workloads, they could make customized 3D assets more practical for consumer applications with frequent user interactions. But the broader opportunity depends on reliability, latency, moderation, privacy safeguards for uploaded photos and the cost of integrating the technology into live services.

For TopTop, the partnership is a test of whether AI-generated 3D content can support repeatable social play. For Viggle, it demonstrates a potential route from AI media creation toward interactive applications. The longer-term measure of success will be whether these experiences deliver durable engagement and commercially viable performance beyond early adopters.

Market Landscape

The launch arrives in a large, competitive gaming market. Newzoo estimates that global games revenue reached $201.6 billion in 2025, up 9.1% year over year, with mobile gaming generating $113.3 billion. Its analysis also points to growing pressure on publishers to improve monetization as user acquisition costs rise.

That environment creates an incentive to experiment with new gameplay loops and personalized content. However, Slap Showdown occupies a different space from conventional mobile games built around established genres: its defining feature is the use of AI-generated 3D characters as interactive game assets.

Viggle’s approach also differs from AI tools focused primarily on generating images or videos. Its physics-native model is designed to represent 3D characters, motion and scenes. Potential competitors and adjacent technologies include game engines, procedural content-generation tools, avatar-creation platforms and other generative AI systems. These are overlapping categories rather than direct equivalents, and their capabilities should be evaluated against specific development requirements.

Strategic Outlook

For TopTop, the next test is whether AI-powered customization translates into sustained engagement across its wider player base. The reported 97% match completion rate is an encouraging early signal, but longer-term retention, repeat play, acquisition costs and monetization would provide a stronger measure of commercial value.

For Viggle, integration into a live social game demonstrates one potential application of world models. Broader adoption will depend on consistent output quality, generation speed, infrastructure costs, moderation and the ability to support diverse devices and gameplay scenarios.

Privacy will also matter. Turning personal photographs into interactive characters introduces questions about consent, image retention, misuse and the handling of generated likenesses. Clear controls and safeguards could become important factors in whether users adopt these features at scale.

The broader opportunity is to make AI-generated content interactive rather than static. Whether that becomes a durable shift in social gaming will depend less on novelty than on how reliably the technology improves the player experience.

Top Insights

• TopTop and Viggle launched Slap Showdown, a multiplayer mini-game that converts uploaded photos into AI-generated 3D characters for interactive social gameplay.

• Viggle’s JST world model powers character generation and movement, connecting physics-based 3D content with real-time player controls rather than limiting AI to media creation.

• TopTop reports a 97% match completion rate, although it has not disclosed the sample size, measurement methodology or independent verification for the first-month figure.

• Viggle says JST-2 generates 3D scenes in seconds for under one U.S. cent, but independent benchmarks and detailed workload assumptions are not included in the announcement.

• Future applications could extend to custom environments and new game mechanics, with retention, monetization, privacy and operating costs determining whether the model scales commercially.

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