Despite growing investments in AI-powered sales technology, most organizations continue to struggle with a fundamental revenue challenge: qualified leads are falling through the cracks. New research from Zapier, the AI orchestration platform, found that 92% of B2B sales and marketing managers report losing qualified leads every month, not because of a lack of software, but because disconnected systems and fragmented workflows prevent timely follow-up. The findings highlight a growing issue facing modern revenue teams as technology adoption accelerates faster than operational integration.

The modern sales technology stack has never been more sophisticated.

Customer relationship management (CRM) platforms, marketing automation tools, conversational AI assistants, lead scoring engines, outreach solutions, and revenue intelligence platforms have become standard components of B2B sales operations. Yet despite unprecedented access to technology, many organizations are still struggling to convert opportunities into revenue.

According to Zapier's latest Dropped Leads Survey, the problem is not the number of tools organizations use but how those tools work together.

The survey of more than 400 U.S. sales and marketing managers found that 92% of respondents experience qualified leads slipping through the cracks every month. More concerning, 38% report that dropped leads occur multiple times each week, while 12% say the issue occurs nearly every day.

The findings suggest that revenue leakage remains a widespread challenge even as organizations continue to expand investments in automation and artificial intelligence.

At the center of the issue is workflow fragmentation.

Many organizations have assembled increasingly complex technology ecosystems consisting of CRM platforms, email engagement systems, marketing automation solutions, AI assistants, and customer data platforms. However, these systems often operate independently, requiring employees to manually move information between applications, update records, assign ownership, and trigger follow-up actions.

As a result, sales representatives frequently become the connective tissue between disconnected systems.

When responsibilities are unclear or information fails to transfer seamlessly between platforms, leads can stagnate in the pipeline before receiving appropriate engagement. In highly competitive markets, even minor delays in response times can significantly reduce conversion rates.

The survey also revealed the operational burden created by manual processes.

Nearly seven in ten managers reported that sales teams spend between three and ten hours each week performing administrative CRM tasks such as entering contact information, updating opportunity stages, and resolving duplicate records. For many organizations, that represents up to one-quarter of a typical workweek spent on activities that do not directly contribute to selling.

These inefficiencies have become increasingly visible as organizations face mounting pressure to improve sales productivity while controlling operational costs.

Another significant challenge identified in the research involves follow-up consistency.

While initial outreach often occurs successfully, 42% of managers reported that their teams fail to complete second or third follow-up attempts. This finding reinforces a long-standing issue in B2B sales, where persistence often plays a critical role in engaging prospects who are evaluating solutions over extended buying cycles.

The study further found that 37% of organizations experience lead loss during handoffs between marketing systems and CRM platforms or between marketing and sales teams. These transition points frequently create visibility gaps that prevent timely engagement and accurate pipeline tracking.

Perhaps the most notable insight from the survey involves artificial intelligence adoption.

The research found that 91% of organizations have already integrated AI into some aspect of their sales workflow, with 55% reporting that AI is fully embedded within lead management processes.

This demonstrates that AI adoption itself is no longer the primary challenge.

Instead, organizations are increasingly focused on orchestrating how multiple AI-powered systems interact across the customer journey. In many cases, one application may score leads, another may generate outreach content, while a third updates CRM records. Without a coordinated workflow connecting these actions, human intervention remains necessary to advance opportunities through the pipeline.

The findings align with broader industry trends.

Research from Gartner and Forrester indicates that revenue operations teams are shifting focus from standalone technology adoption toward workflow automation, process orchestration, and system interoperability. As technology stacks expand, organizations are discovering that operational efficiency depends less on individual tools and more on how effectively those tools exchange information and automate actions.

This evolution has contributed to the emergence of AI orchestration platforms, which aim to coordinate workflows across multiple applications while reducing manual intervention.

According to the survey, respondents identified integration as a higher priority than additional technology investments. More than half of managers cited better connectivity across CRM, email, calendar, and marketing platforms as their most pressing need. Others emphasized automated follow-up processes, intelligent task creation, and automated lead routing as critical areas for improvement.

For revenue leaders, the implications are clear.

Organizations that continue adding software without addressing workflow connectivity may see diminishing returns from technology investments. Conversely, businesses that prioritize process automation, AI orchestration, and system integration can improve response times, reduce administrative overhead, and increase the likelihood that qualified leads receive timely engagement.

As AI becomes a permanent fixture within sales and marketing operations, competitive differentiation may increasingly depend on workflow execution rather than tool adoption alone. Zapier's findings suggest that the future of revenue growth lies not in acquiring more technology, but in ensuring that existing technologies work together as a unified system.

Market Landscape

The global revenue operations and sales technology market is evolving rapidly as organizations seek to improve productivity, automate repetitive tasks, and accelerate pipeline growth. Gartner research shows that automation, workflow orchestration, and AI-enabled sales processes remain among the highest-priority investments for revenue leaders.

At the same time, enterprises are managing increasingly complex technology environments that include CRM platforms, marketing automation systems, customer data platforms, conversational AI tools, and analytics solutions. This complexity has elevated integration and interoperability as critical success factors.

As AI adoption becomes mainstream, organizations are shifting attention toward orchestration platforms capable of connecting systems, automating workflows, and improving cross-functional alignment between sales and marketing teams.

Top Insights

• Zapier's survey found that 92% of sales and marketing managers report losing qualified leads every month.
• Nearly 40% of respondents experience dropped leads multiple times each week.
• Sales representatives spend between three and ten hours weekly on CRM administration and data management tasks.
• Forty-two percent of organizations struggle to maintain follow-up beyond the initial prospect interaction.
• Ninety-one percent of respondents have incorporated AI into sales workflows, yet workflow fragmentation remains a major challenge.
• Sales leaders increasingly prioritize integration, automation, and workflow orchestration over acquiring additional tools

Get in touch with our MarTech Experts

As artificial intelligence reshapes every aspect of marketing, from content creation and campaign execution to customer engagement and analytics, the demand for AI-literate marketing professionals is accelerating. In response, Adobe and LinkedIn have unveiled AI Essentials for Marketers, a global learning initiative designed to help marketers develop practical AI skills through role-based, accessible training. The partnership reflects a broader industry shift toward workforce transformation, as organizations seek to equip teams with the capabilities needed to succeed in an increasingly AI-driven marketing landscape.

Artificial intelligence is no longer an experimental technology within marketing organizations. It is becoming a core component of how brands create content, personalize customer experiences, optimize campaigns, and analyze performance.

Recognizing the growing skills gap between AI adoption and workforce readiness, Adobe and LinkedIn have announced AI Essentials for Marketers, a global education initiative aimed at helping marketing professionals build the competencies required to work effectively alongside AI technologies.

The program arrives at a pivotal moment for the industry.

According to data from LinkedIn’s Economic Graph, AI skills have emerged as the leading area of professional development for marketers. The platform also reports that marketing job postings requiring AI literacy have increased by 113% year-over-year, signaling that employers increasingly view AI proficiency as a critical business skill rather than a specialized technical capability.

This shift reflects a broader transformation occurring across the marketing ecosystem.

Generative AI and emerging agentic AI systems are changing how marketers approach content strategy, creative production, audience segmentation, campaign management, customer journey orchestration, and performance measurement. As organizations integrate AI into daily operations, the need for workforce upskilling has become a strategic priority for chief marketing officers and business leaders.

The Adobe-LinkedIn initiative seeks to address this challenge through a practical, role-specific learning model designed for modern professionals.

Rather than relying on lengthy certification programs, AI Essentials for Marketers delivers short-form learning experiences that fit into busy work schedules. The courses are designed by marketers for marketers, enabling participants to develop applicable skills without requiring significant time away from their day-to-day responsibilities.

The initiative will feature four role-based learning tracks covering some of the most in-demand functions within modern marketing organizations. These include digital marketing, content and creative operations, social media and communications, as well as data and analytics.

Importantly, the courses will be available in 47 languages, significantly expanding access for marketing professionals across global markets.

The program combines the strengths of both organizations.

Adobe brings extensive expertise in marketing technology, creative tools, customer experience management, and enterprise AI adoption. The company reports that 99% of Fortune 100 organizations use AI within Adobe applications, demonstrating the scale at which AI has become embedded within enterprise marketing environments.

Meanwhile, LinkedIn contributes its learning infrastructure, labor market intelligence, and professional development ecosystem. Through LinkedIn Learning, users gain access to a vast catalog of educational resources, including more than 2,300 AI-focused courses designed to support career growth and workforce development.

Together, the companies aim to bridge the gap between AI awareness and practical implementation.

The initiative goes beyond theoretical instruction by incorporating real-world customer use cases, expert perspectives, marketing research, and hands-on learning experiences. Participants will learn how AI can support content planning, creative production, campaign execution, audience targeting, and data-driven decision-making.

This emphasis on applied learning is becoming increasingly important as organizations move from AI experimentation toward operational deployment.

Many enterprises have already implemented generative AI tools for content generation and productivity enhancement. However, industry analysts increasingly argue that long-term success depends on developing organizational capabilities alongside technological investments.

Without appropriate training, companies risk underutilizing AI platforms or creating inconsistent adoption across teams.

The launch also aligns with Adobe’s broader workforce development efforts through Adobe Digital Academy and Experience League, which focus on expanding access to digital skills, creative education, and career advancement opportunities. Adobe has committed more than $100 million through scholarships, product access, donations, and partnerships aimed at supporting learners from diverse backgrounds.

For LinkedIn, the initiative further strengthens its position as a platform connecting professional development with evolving labor market demands.

As AI continues to reshape job requirements, skills validation is becoming increasingly valuable for professionals seeking career advancement. Participants who complete the courses will receive certificates that can be displayed directly on their LinkedIn profiles, helping demonstrate expertise to employers and recruiters.

Beyond individual career growth, the partnership reflects a larger industry trend.

Organizations are beginning to recognize that AI transformation is not solely a technology initiative. It is also a talent strategy. As marketing teams adopt increasingly sophisticated AI-powered workflows, businesses must invest in workforce readiness to maximize returns on technology investments.

The future of marketing will likely be defined not by whether companies adopt AI, but by how effectively their people learn to collaborate with it.

Through AI Essentials for Marketers, Adobe and LinkedIn are positioning themselves at the center of that transformation, providing marketers with the skills needed to navigate the next generation of customer engagement, creativity, and digital innovation.

Market Landscape

The global market for AI-powered marketing technologies continues to expand as organizations seek greater efficiency, personalization, and customer engagement. Research from Gartner, Forrester, and IDC indicates that generative AI and agentic AI are among the most influential technologies shaping the future of marketing operations.

At the same time, employers are facing growing pressure to upskill workforces as AI becomes embedded across business functions. Marketing professionals increasingly require competencies that combine creativity, data literacy, automation expertise, and AI proficiency. This has created significant demand for accessible learning programs focused on practical AI applications within real-world marketing environments.

Top Insights

• Adobe and LinkedIn have launched AI Essentials for Marketers, a global AI skills development initiative.
• LinkedIn data shows marketing job postings requiring AI literacy skills have increased by 113% year-over-year.
• The program offers role-based learning tracks focused on digital marketing, content creation, communications, and analytics.
• Courses will be available in 47 languages to support global workforce development.
• Participants will gain practical experience in AI-powered content creation, campaign development, audience targeting, and data analysis.
• The initiative reflects a growing industry focus on workforce readiness as AI adoption accelerates

Get in touch with our MarTech Experts

The race to modernize multifamily housing operations is accelerating as property technology providers increasingly embed artificial intelligence into marketing, leasing, and resident engagement workflows. Ahead of the Apartmentalize 2026 conference in New Orleans, 365 Connect announced new advancements to its autonomous marketing and leasing platform, positioning AI-driven automation as a central component of the next generation of apartment operations.

The multifamily housing industry is entering a new phase of digital transformation, driven by rising operational costs, evolving renter expectations, and growing pressure to improve leasing efficiency. Against this backdrop, 365 Connect revealed plans to showcase its latest AI-powered platform innovations during the upcoming Apartmentalize conference, one of the industry's largest gatherings focused on apartment housing technology and operations.

At the center of the announcement is the company's Search-to-Sofa® platform, a technology ecosystem designed to unify marketing automation, renter discovery, leasing workflows, and resident engagement into a single operational environment. The platform aims to automate tasks that traditionally require extensive manual effort from property management teams, ranging from digital marketing execution to lease generation and move-in documentation.

The announcement reflects a broader trend unfolding across the property technology (PropTech) sector. Organizations are increasingly exploring how artificial intelligence can reduce administrative overhead while improving customer experiences. Similar to how companies such as Salesforce, Adobe, Microsoft, and Google are embedding generative AI into enterprise workflows, multifamily technology vendors are applying automation to leasing, marketing, and resident communications.

According to 365 Connect, its latest platform capabilities continuously generate and distribute marketing content across search and social media channels while optimizing content for AI-driven discovery environments. As search behavior evolves beyond traditional search engines toward AI-powered assistants and conversational discovery platforms, property operators are increasingly looking for technologies that improve visibility across both conventional and emerging digital channels.

One of the more notable aspects of the company's announcement is its emphasis on AI-discovery-optimized content. This reflects a growing industry focus on Generative Engine Optimization (GEO), where content is structured to improve visibility within AI-generated responses from platforms such as ChatGPT, Google Gemini, and other conversational search environments. For multifamily operators competing in crowded rental markets, discoverability has become an increasingly important factor in lead generation.

Beyond marketing automation, 365 Connect is also highlighting advancements in autonomous lease execution. The platform can automatically generate lease agreements, addendums, and move-in documentation immediately following renter screening approvals. By reducing document preparation time from hours to seconds, the company aims to address one of the most labor-intensive components of the leasing process.

The move aligns with broader industry efforts to automate transaction-heavy workflows. Enterprise software vendors across sectors are increasingly using AI agents and workflow automation to accelerate business processes, reduce manual intervention, and improve operational consistency. In multifamily housing, where staffing shortages and operational efficiency remain ongoing concerns, these capabilities could offer measurable productivity gains.

Industry analysts continue to highlight automation as a key investment area. According to research from Gartner, organizations are accelerating AI adoption to improve operational efficiency and employee productivity. Meanwhile, McKinsey & Company estimates that generative AI could contribute trillions of dollars in annual economic value across industries through workflow automation and knowledge-based task optimization.

For apartment operators, the business case is becoming increasingly clear. Leasing teams often juggle marketing management, prospect engagement, application processing, lease preparation, and resident communications simultaneously. Platforms capable of autonomously handling portions of these workflows could allow staff to focus on higher-value interactions while maintaining faster response times and improved service levels.

Competition in the multifamily technology market is also intensifying. Vendors are moving beyond standalone leasing software and resident portals toward integrated platforms that combine marketing technology, customer engagement, analytics, and operational automation. The industry's direction increasingly mirrors developments seen in enterprise MarTech and SaaS ecosystems, where unified platforms are replacing fragmented point solutions.

Apartmentalize 2026 is expected to provide a significant stage for these conversations. As property operators evaluate how AI can be deployed responsibly and effectively, technology providers are racing to demonstrate practical applications that deliver measurable business outcomes rather than experimental capabilities.

For 365 Connect, the announcement signals a strategic focus on autonomous operations as the next frontier of multifamily innovation. Whether the broader industry embraces fully autonomous marketing and leasing workflows at scale remains to be seen, but the company's latest platform enhancements underscore a growing belief that AI-powered execution will play an increasingly prominent role in the future of apartment management.

Market Landscape

The multifamily housing technology sector is rapidly converging with broader enterprise MarTech, SaaS, and AI automation trends. Property operators are seeking platforms that unify lead generation, digital marketing, resident engagement, leasing automation, and analytics into a single ecosystem. As generative AI reshapes customer acquisition and operational workflows, vendors are increasingly building autonomous capabilities that can execute tasks with minimal human intervention.

The emergence of AI-driven leasing platforms mirrors similar transformations occurring across CRM, marketing automation, and customer experience platforms from industry leaders such as Salesforce, Adobe, Microsoft, and Google. The next phase of PropTech innovation is likely to focus on intelligent automation, predictive engagement, and AI-powered operational orchestration.

Top Insights

•  365 Connect is expanding its AI-powered Search-to-Sofa platform to automate multifamily marketing, renter engagement, and lease execution within a unified operational environment.
• The company is emphasizing AI-discovery optimization, helping apartment communities improve visibility across emerging conversational search and generative AI ecosystems.
• Autonomous lease generation capabilities aim to reduce administrative workloads by instantly creating leasing documents following applicant approval.
• The announcement reflects a broader PropTech trend toward intelligent automation as property operators seek efficiency gains and improved resident experiences.
• Multifamily technology platforms are increasingly adopting enterprise-grade AI strategies similar to those being implemented across CRM, marketing automation, and SaaS ecosystems.

Get in touch with our MarTech Experts

For years, one-to-one personalization has been one of digital marketing's most ambitious promises. While brands have invested heavily in customer data platforms, marketing automation tools, and account-based marketing programs, most personalization efforts have remained limited to audience segments rather than true individual experiences. Optimizely is aiming to change that equation with a new AI-powered capability designed to help enterprises create and maintain personalized content experiences at scale.

As marketers face increasing pressure to deliver more relevant digital experiences across expanding customer journeys, Optimizely has announced a new capability called Limitless 1:1 Personalization. Introduced as part of the company's Optimizely Opal AI platform, the technology is designed to help marketing teams create individualized digital experiences for customers, prospects, and buying committees without dramatically increasing content production workloads.

The launch addresses a longstanding challenge within digital marketing. Despite years of investment in personalization technologies, most organizations still rely on segmentation models that group users based on shared characteristics. While effective for broad targeting, these approaches often fail to reflect the unique context, interests, and intent signals of individual buyers.

According to Optimizely, its new capability moves beyond traditional segmentation by combining audience intelligence, content automation, and AI-driven orchestration to dynamically generate tailored digital experiences. The platform analyzes existing content libraries, customer relationship management (CRM) data, product information, audience segments, and external research sources before assembling personalized content experiences aligned to specific user profiles.

The announcement comes at a time when enterprises are rapidly increasing investments in artificial intelligence and customer experience technologies. Research from Gartner suggests that personalization remains one of the highest-priority initiatives for digital marketing leaders, while studies from McKinsey & Company have found that organizations excelling at personalization can generate significantly higher revenue growth compared with peers.

A major focus of the new offering is the middle of the customer journey, where prospects are actively evaluating products and vendors. In many B2B buying environments, multiple stakeholders participate in purchasing decisions, each with different priorities and information requirements. A chief financial officer evaluating budget impact, for example, often requires different content than an IT leader assessing implementation complexity.

Optimizely's platform seeks to address this challenge through flexible audience modeling. Marketing teams can create content experiences tailored to specific members of a buying committee, including economic buyers, technical evaluators, business champions, and operational stakeholders. Rather than building each experience manually, AI agents generate and maintain personalized content assets using existing brand-approved materials.

The capability extends beyond B2B use cases. Consumer-facing organizations in retail, travel, financial services, and e-commerce can create personalized landing pages, product experiences, and customer journeys based on factors such as geographic location, behavioral intent, product interests, and demographic attributes.

One of the more significant aspects of the launch is its focus on operational scalability. Personalization has traditionally struggled because creating thousands of individualized experiences requires substantial content resources and ongoing maintenance. Optimizely's approach leverages autonomous agents to continuously monitor data sources, update content, and optimize experiences as customer information changes.

The platform includes content auditing capabilities that identify outdated assets, messaging gaps, and inconsistencies before new experiences are created. Audience intelligence models then aggregate information from customer databases, product catalogs, behavioral signals, and external research sources to construct detailed audience profiles.

Another notable feature is governance management. Enterprise marketing teams often hesitate to automate content creation due to concerns around brand consistency, compliance, and accuracy. Optimizely addresses this challenge through a progressive trust model that allows organizations to maintain human review processes before gradually increasing AI autonomy as confidence grows.

The company also integrates the capability directly into its content management ecosystem, enabling personalized experiences to be published as searchable, crawlable pages within brand-owned domains. This approach aligns with emerging Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO) strategies, which seek to improve visibility across AI-powered discovery platforms, including conversational search environments.

The launch further strengthens Optimizely One, the company's unified digital experience platform that combines content management, customer data, experimentation, and campaign operations into a connected ecosystem. By integrating AI-driven personalization directly into these workflows, Optimizely is positioning itself against broader enterprise experience providers such as Adobe, Salesforce, Microsoft, and Google.

The broader significance of the announcement extends beyond content generation. As generative AI matures, the competitive advantage is shifting from creating content at scale to delivering relevant, context-aware experiences that adapt continuously to customer behavior and intent.

For enterprise marketing teams, the next phase of personalization may no longer be defined by audience segments. Instead, it could be measured by an organization's ability to create individualized experiences that remain accurate, relevant, and optimized throughout the customer lifecycle. Optimizely's latest launch reflects how quickly that vision is moving from aspiration to operational reality.

Market Landscape

The personalization technology market is undergoing rapid transformation as generative AI reshapes how brands engage customers. Traditional segmentation-based marketing is increasingly giving way to dynamic audience intelligence models powered by customer data platforms (CDPs), AI agents, and predictive analytics.

Industry leaders including Adobe, Salesforce, Microsoft, and Google continue to invest heavily in AI-powered customer experience platforms. At the same time, marketers are seeking solutions that unify content management, experimentation, audience intelligence, and marketing automation into a single operational framework.

As enterprise organizations pursue account-based marketing, omnichannel engagement, and AI-driven customer journeys, scalable one-to-one personalization is emerging as a key battleground in the digital experience platform market.

Top Insights

• Optimizely introduced Limitless 1:1 Personalization, enabling enterprises to generate individualized customer experiences using AI-driven audience intelligence and content orchestration.
• The platform automates the creation and maintenance of account-specific microsites, personalized landing pages, and tailored customer journeys across B2B and B2C environments.
• AI agents continuously monitor customer data, engagement signals, and content performance to keep experiences relevant without extensive manual intervention.
• Governance controls allow organizations to balance automation with compliance, brand consistency, and human oversight as AI adoption expands.
• The launch strengthens Optimizely's position in the growing digital experience platform market where AI-driven personalization is becoming a competitive differentiator.

Get in touch with our MarTech Experts

Artificial intelligence has become a boardroom priority, and few business functions are feeling the pressure more intensely than marketing. While most chief marketing officers believe AI is fundamentally reshaping how brands engage customers, a new report from Boston Consulting Group suggests many marketing organizations remain in the early stages of transformation. The findings highlight a growing disconnect between AI ambitions and operational reality as enterprises race to build agentic marketing capabilities.

The marketing industry has spent the past two years embracing generative AI, experimenting with content automation, predictive analytics, and customer engagement tools. Yet according to Boston Consulting Group's latest report, How CMOs Are Moving Agentic Marketing from Illusion to Reality, most organizations have yet to move beyond isolated AI deployments into fully integrated marketing operations.

The study, based on a survey of 300 CMOs across B2B and B2C organizations alongside interviews with 50 marketing leaders, found that while AI enthusiasm is widespread, enterprise-wide transformation remains limited. Only 8% of CMOs report running campaigns where multiple AI agents operate autonomously across workflows. Less than one-third say they have transformed significant portions of their marketing function using agent-based systems.

Instead, many organizations continue to use generative AI primarily as a productivity tool. Approximately 42% of respondents said AI is currently deployed as an assistant for individual tasks within a limited number of workflows rather than as part of a coordinated operational framework.

The findings arrive as marketing leaders face growing expectations from executive teams. Nearly all CMOs surveyed—94%—said CEO expectations of marketing have increased significantly over the past two years. At the same time, marketing leaders are taking greater ownership of AI investment decisions within their organizations, with roughly half reporting that marketing now leads AI spending and deployment strategies.

This shift signals a broader evolution in the role of the CMO. Historically responsible for brand strategy, demand generation, and customer engagement, marketing leaders are increasingly becoming architects of enterprise AI transformation. However, the report suggests many organizations are still struggling to build the infrastructure required to support that responsibility.

A key challenge is the transition from generative AI tools to agentic marketing systems. While generative AI can create content, summarize information, or assist with campaign execution, agentic AI introduces a higher level of automation by enabling multiple AI agents to coordinate activities, make decisions, and execute workflows with limited human intervention.

According to BCG, this evolution requires far more than deploying standalone AI applications. Successful organizations are building connected operating environments that combine customer data, marketing technology platforms, orchestration layers, governance frameworks, and specialized AI models into unified systems capable of supporting end-to-end marketing execution.

The report points to a growing realization among marketing executives that data infrastructure and martech modernization are becoming foundational investments. Martech and data platforms emerged as the top AI investment priority among surveyed CMOs, rising significantly compared with 2025 spending patterns.

This trend reflects a broader shift occurring across enterprise technology markets. Organizations increasingly recognize that AI performance depends on the quality and accessibility of underlying data. Customer data platforms, marketing automation systems, CRM environments, and analytics platforms are becoming critical enablers of agentic workflows.

The financial commitment is also accelerating. Nearly 43% of surveyed CMOs reported annual AI investments exceeding $15 million, compared with just 28% a year earlier. Among the highest-spending organizations, more than four in ten are substantially increasing investment in workflow orchestration technologies designed to connect multiple AI systems across marketing operations.

Early adopters are beginning to see measurable business outcomes. Approximately 31% of B2C marketing leaders and 20% of B2B CMOs reported significant revenue impact from their agentic marketing initiatives. Benefits cited include improved campaign speed, greater operational efficiency, faster content production cycles, and stronger customer engagement outcomes.

Yet technology alone is not proving to be the most difficult hurdle.

The report identifies talent development as the largest barrier to successful AI transformation. As marketing organizations introduce AI-driven operating models, many are discovering that traditional marketing skill sets are insufficient for managing increasingly autonomous systems.

Around 80% of surveyed CMOs said they are making substantial investments in AI-focused workforce development programs. Similar numbers are expanding responsible AI and ethics training initiatives, reflecting growing concerns around governance, compliance, transparency, and brand protection.

The emergence of agentic marketing is also reshaping organizational design. Leading enterprises are creating new roles focused on AI operations, automation strategy, data governance, and workflow orchestration. Teams are being restructured around AI-enabled processes rather than traditional channel-based functions.

The broader significance of the report extends beyond marketing departments. As organizations adopt AI across sales, customer service, operations, and finance, marketing increasingly serves as a testing ground for autonomous workflows. The lessons learned from agentic marketing deployments could influence how AI operating models evolve across the wider enterprise.

Technology providers including Salesforce, Adobe, Microsoft, and Google are rapidly expanding agentic AI capabilities across their platforms, signaling that enterprise software is moving toward increasingly autonomous operational models.

For CMOs, the message from BCG's findings is clear. While generative AI experimentation is widespread, competitive differentiation may increasingly depend on an organization's ability to build connected agentic ecosystems capable of executing marketing activities at scale. The gap between AI adoption and AI transformation remains substantial, but it is narrowing as marketing leaders move from pilots to enterprise-wide operational redesign.

Market Landscape

The emergence of agentic marketing represents the next stage of AI maturity within the MarTech ecosystem. After an initial wave focused on generative AI content creation, organizations are now exploring autonomous workflows that connect customer data, campaign management, analytics, experimentation, and personalization into coordinated systems.

According to industry research from Gartner, AI remains among the highest-priority investment areas for marketing leaders. Meanwhile, IDC forecasts continued growth in enterprise AI spending as organizations seek operational efficiency and competitive advantage. The convergence of AI agents, customer data platforms, marketing automation, and workflow orchestration technologies is creating a new category of intelligent marketing infrastructure designed to support end-to-end decision-making and execution.

Top Insights

• BCG found that only 8% of CMOs currently operate campaigns using multiple autonomous AI agents despite widespread belief that AI is transforming marketing.
• Nearly half of surveyed CMOs now lead AI investment decisions within marketing, reflecting the growing strategic importance of AI-driven customer engagement.
• Martech and data infrastructure have become the top AI investment priority as organizations build foundations for scalable agentic marketing operations.
• Early adopters report measurable revenue gains, faster campaign execution, and improved operational efficiency from AI-powered workflow orchestration.
• Talent development remains the largest challenge, with most organizations investing heavily in AI upskilling, governance programs, and organizational redesign.

Get in touch with our MarTech Experts

As intellectual property disputes, class action lawsuits, and consumer protection cases increasingly rely on data-driven evidence, the role of consumer behavior research in litigation continues to grow. Against this backdrop, Applied Marketing Science (AMS) has expanded its litigation support capabilities by adding consumer behavior and conjoint analysis specialist Dr. Suneal Bedi to its network of affiliated expert witnesses.

The intersection of marketing science, consumer behavior, and legal strategy is becoming increasingly important as courts and regulatory bodies place greater emphasis on empirical evidence in complex litigation. Recognizing this trend, Applied Marketing Science (AMS) has announced the addition of Dr. Suneal Bedi to its expanding network of litigation survey experts.

The appointment strengthens AMS's capabilities in areas where consumer research and legal proceedings increasingly overlap, particularly in intellectual property disputes, class action litigation, marketing law, and business ethics cases.

Dr. Bedi currently serves as an Associate Professor of Business Law and Ethics and Jerome Bess Faculty Fellow at the Indiana University Kelley School of Business. His academic work spans intellectual property law, consumer behavior, litigation finance, business ethics, and marketing regulation, disciplines that have become increasingly interconnected as businesses navigate evolving legal and consumer environments.

The move comes as organizations face growing scrutiny over branding practices, product claims, consumer communications, and intellectual property rights. In many of these disputes, courts rely on survey-based evidence and consumer perception research to assess issues such as trademark confusion, brand recognition, advertising impact, and consumer decision-making.

One of Dr. Bedi's key areas of specialization is conjoint analysis, a quantitative research methodology widely used to evaluate how consumers value specific product attributes. Originally developed for marketing research, conjoint analysis has become a valuable tool in litigation, particularly in cases involving damages estimation, intellectual property valuation, product differentiation, and consumer preference measurement.

For legal teams, the methodology offers a structured way to quantify how specific product features, brand elements, or market factors influence purchasing decisions. As courts increasingly seek evidence grounded in behavioral science and statistical rigor, experts capable of designing and defending these studies have become highly sought after.

Beyond his litigation work, Dr. Bedi's academic research examines the broader relationship between law, business, and public policy. His studies combine experimental methods, quantitative analysis, and philosophical frameworks to explore how legal systems interact with marketplace behavior. This multidisciplinary approach reflects a broader trend within legal and business research, where complex disputes often require expertise that extends beyond traditional legal interpretation.

The addition also reflects AMS's continued investment in litigation support services. The firm has built a reputation for applying market research methodologies to legal proceedings, helping law firms, corporations, and courts evaluate consumer perception and marketplace evidence. Survey research, consumer confusion studies, and behavioral analysis have become increasingly important in intellectual property and consumer protection litigation, particularly as digital commerce and online branding create new legal challenges.

Industry experts note that litigation involving trademarks, patents, advertising claims, and class action disputes has become more data-intensive over the past decade. As organizations generate larger volumes of customer and market data, attorneys increasingly rely on expert testimony supported by advanced analytics, survey methodologies, and behavioral science.

The growing use of expert witnesses in these areas mirrors broader developments across industries where data-driven decision-making is becoming a standard requirement. Research from organizations such as Gartner and McKinsey & Company has consistently highlighted the importance of analytics and evidence-based strategies in business decision-making, a trend that is extending into legal and regulatory environments.

Dr. Bedi brings an unusually interdisciplinary background to this work. He earned a Ph.D. and M.S. in Marketing from the The Wharton School, a J.D. from Harvard Law School, and a bachelor's degree in economics from Swarthmore College. This combination of legal, economic, and marketing expertise positions him to address disputes that require both scientific analysis and legal interpretation.

His research has appeared in leading academic publications, including the New York University Law Review, Cornell Law Review, Vanderbilt Law Review, the Harvard Journal of Law & Technology, the Journal of Business Ethics, and the Journal of Marketing Research. He has also contributed commentary and analysis to mainstream publications including The New York Times, Forbes, U.S. News & World Report, and the San Francisco Chronicle.

For AMS, the addition represents more than an expansion of its expert witness network. It reflects a growing demand for professionals who can bridge the gap between consumer psychology, marketing science, and legal strategy. As litigation increasingly incorporates behavioral evidence, survey analytics, and quantitative modeling, firms capable of providing scientifically defensible expertise are likely to play a larger role in complex legal proceedings.

The appointment underscores a broader shift occurring across legal and business disciplines: the growing importance of consumer insight and data science as critical components of modern litigation support.

Market Landscape

The litigation consulting market is increasingly incorporating advanced market research methodologies, behavioral science, and data analytics into legal proceedings. Intellectual property disputes, consumer protection cases, advertising litigation, and class action lawsuits frequently depend on empirical evidence to establish consumer perception, damages, and marketplace impact.

Conjoint analysis, survey research, and consumer behavior modeling have become important tools in legal strategy, particularly as courts seek objective, statistically valid evidence. As businesses continue to operate in highly competitive and digitally driven environments, demand for expert witnesses with expertise spanning law, marketing, and analytics is expected to grow.

Top Insights

• AMS has expanded its litigation support practice by adding consumer behavior and conjoint analysis expert Dr. Suneal Bedi to its affiliated expert network.
• Dr. Bedi specializes in intellectual property disputes, class action litigation, business ethics, and consumer behavior research supported by quantitative methodologies.
• Conjoint analysis is becoming increasingly important in litigation as courts seek measurable evidence regarding consumer preferences, damages, and product valuation.
• The appointment reflects rising demand for expert witnesses who can combine legal expertise with marketing science and behavioral analytics.
• Organizations facing trademark, advertising, and consumer protection disputes are increasingly relying on survey-based evidence and consumer research methodologies.

Get in touch with our MarTech Experts

The race to build AI infrastructure is increasingly becoming a global competition for power, data center capacity, and strategic geographic positioning. As demand for AI training and inference workloads continues to surge, infrastructure providers are expanding beyond domestic markets to secure energy resources and accelerate deployment timelines. In its latest move, IREN has entered Europe through the acquisition of Spain-based Nostrum Group, significantly expanding its AI cloud and data center development platform.

IREN Limited has completed its acquisition of Ingenostrum S.L., known as Nostrum Group, marking the company's first major expansion into the European AI infrastructure market.

The deal adds approximately 490 megawatts (MW) of secured, grid-connected power capacity across Spain, alongside an additional development pipeline and a specialized workforce of more than 50 employees spanning engineering, construction, development, and operations.

The acquisition comes at a pivotal moment for the artificial intelligence industry. Rapid growth in large language models, generative AI applications, enterprise AI adoption, and inference workloads has intensified demand for high-performance computing infrastructure. Data center operators worldwide are competing to secure power capacity and suitable locations capable of supporting next-generation GPU clusters and AI cloud services.

For IREN, the acquisition provides immediate access to one of Europe's emerging AI infrastructure hubs. Spain has become increasingly attractive to data center developers due to its growing renewable energy generation capacity, expanding fiber connectivity, and favorable geographic position for serving European markets.

The move reflects a broader industry trend in which infrastructure providers are prioritizing access to energy as a strategic competitive advantage. AI workloads require significantly more computational power than traditional enterprise applications, creating unprecedented demand for electricity and data center resources.

According to research from International Energy Agency, electricity consumption from data centers is expected to rise substantially as artificial intelligence adoption accelerates. Industry analysts at Gartner and IDC have similarly identified AI infrastructure as one of the fastest-growing segments within enterprise technology spending.

Nostrum's existing portfolio gives IREN a significant foothold in Europe without requiring the lengthy development timelines typically associated with greenfield infrastructure projects. By acquiring an established developer with secured power agreements and local expertise, IREN can accelerate deployment while reducing some of the regulatory and operational complexities often associated with entering new markets.

The acquisition also highlights the increasing importance of regional AI cloud providers. While hyperscale cloud vendors such as Amazon Web Services, Microsoft, and Google continue to dominate the global cloud market, demand for specialized AI infrastructure has created opportunities for independent providers focused specifically on GPU-intensive workloads.

IREN has positioned itself as a vertically integrated AI cloud provider, combining data center development, power infrastructure, and AI computing resources within a unified operating model. This approach allows the company to control critical infrastructure components while addressing growing enterprise demand for AI training and inference services.

The strategic value of Nostrum extends beyond its existing assets. The company has spent years developing relationships with local stakeholders, securing power resources, and building a pipeline of future projects. These capabilities may prove increasingly valuable as competition for energy access intensifies across Europe.

The acquisition also reflects broader investment activity across the AI infrastructure ecosystem. Over the past two years, technology companies, cloud providers, private equity firms, and infrastructure investors have committed billions of dollars toward data centers, GPU deployments, and energy projects designed to support artificial intelligence growth.

Research from McKinsey & Company estimates that AI infrastructure investment requirements could reach hundreds of billions of dollars over the coming decade as organizations scale generative AI deployments and advanced computing environments.

Europe represents a particularly important market in this landscape. Enterprises across the region are accelerating AI adoption while policymakers seek to strengthen digital sovereignty and expand domestic technology infrastructure. As a result, demand for locally hosted AI computing capacity continues to increase.

For Nostrum, joining a larger infrastructure platform may provide the capital and operational scale required to accelerate project development. For IREN, the acquisition delivers immediate market access, a substantial power portfolio, and a foundation for future European expansion.

As AI infrastructure becomes one of the most strategically important technology sectors globally, acquisitions like this underscore a critical reality: access to power, land, connectivity, and engineering expertise is becoming just as important as access to advanced AI models themselves. The companies that can secure and scale these resources are likely to play a central role in the next phase of AI-driven digital transformation.

Market Landscape

The AI infrastructure market is experiencing unprecedented growth as enterprises deploy generative AI, machine learning, and large-scale inference workloads. Data center operators are racing to secure power capacity, renewable energy resources, and high-speed network connectivity to support GPU-intensive computing environments.

Major technology companies including Microsoft, Google, Amazon, and emerging AI cloud providers are investing heavily in data center expansion. Europe has become a strategic growth region due to rising enterprise AI adoption, government support for digital infrastructure, and growing demand for localized cloud services.

Power availability has emerged as one of the industry's most important competitive differentiators, driving acquisitions, partnerships, and infrastructure investments across global markets.

Top Insights

• IREN has completed the acquisition of Spain-based Nostrum Group, gaining approximately 490MW of secured grid-connected power capacity for AI infrastructure development.
• The transaction marks IREN's entry into the European market and strengthens its ability to serve growing demand for AI training and inference workloads.
• Spain's renewable energy resources and connectivity infrastructure are making the country an increasingly attractive location for AI data center expansion.
• The acquisition highlights how access to power infrastructure is becoming a critical strategic asset in the global AI cloud market.
• Demand for AI computing capacity continues to drive investment across data centers, cloud infrastructure, and high-performance computing ecosystems.

Get in touch with our MarTech Experts

As generative AI platforms increasingly shape how business buyers discover, evaluate, and shortlist vendors, traditional search visibility is no longer the only factor influencing market presence. Organizations are now competing to become trusted sources within AI-generated responses, where credibility signals, earned media, and third-party validation often determine visibility. Responding to this shift, Plat4orm and Edge Marketing have announced a strategic partnership designed to help organizations strengthen authority across AI-powered search and discovery environments.

The rise of generative AI is transforming enterprise buying behavior, forcing marketing and communications leaders to rethink how organizations build visibility and trust. In response to this evolving landscape, Plat4orm and Edge Marketing have formed a strategic partnership aimed at helping organizations improve their presence within AI-driven search and discovery ecosystems.

At the center of the partnership is the launch of the Trusted Answer Growth System™, a framework designed to align strategic communications, earned media, content strategy, answer engine optimization (AEO), and demand generation into a unified market visibility strategy.

The initiative reflects a broader transformation underway in B2B marketing. Buyers are increasingly using AI-powered assistants and search platforms such as OpenAI's ChatGPT, Anthropic's Claude, and Google's Gemini to research solutions, compare vendors, and validate purchasing decisions before engaging with sales teams.

This shift is changing the mechanics of brand discovery. Rather than relying solely on traditional search rankings or paid advertising, organizations are finding that AI systems increasingly surface information based on authority indicators such as media coverage, expert commentary, analyst references, citations from trusted publications, and broader digital reputation signals.

The implications for marketers are significant. While search engine optimization remains important, visibility in AI-generated responses requires a broader strategy focused on trust, credibility, and authoritative content.

According to recent research cited by the firms, more than 95% of links surfaced in AI-generated answers originate from non-paid sources. This suggests that earned media, industry recognition, and third-party validation may play a larger role in influencing AI-driven visibility than traditional advertising channels.

The Trusted Answer Growth System™ seeks to address this challenge by helping organizations coordinate functions that have historically operated independently. Public relations, content marketing, demand generation, search optimization, analyst relations, and brand positioning efforts are brought together under a common objective: increasing the likelihood that an organization becomes the trusted answer buyers encounter during research.

The process begins with a Trust Signal Review™, which evaluates how a company currently appears across digital channels, media coverage, search results, and AI-assisted discovery environments. From there, organizations receive recommendations designed to strengthen visibility, improve message consistency, and enhance authority signals across multiple buyer touchpoints.

Industry analysts have increasingly highlighted the importance of this evolution. Research from Forrester has shown growing adoption of AI throughout enterprise purchasing journeys, while studies from Gartner continue to demonstrate the expanding role of digital self-service research in B2B decision-making.

For marketing leaders, this creates both opportunities and challenges. The traditional marketing funnel is becoming less linear as buyers consume information across multiple channels simultaneously. AI systems are further accelerating this trend by aggregating information from numerous sources and presenting synthesized recommendations to users.

As a result, organizations can no longer rely solely on owned channels such as websites, blogs, or product pages to establish market authority. Instead, credibility increasingly depends on how the broader ecosystem—including journalists, analysts, industry experts, and third-party publications—describes and references a brand.

The partnership between Plat4orm and Edge Marketing is particularly focused on organizations operating in regulated industries and complex B2B markets, where trust and reputation often play a decisive role in purchasing decisions. Industries such as financial services, healthcare, cybersecurity, legal services, and enterprise technology face growing pressure to establish authoritative digital footprints that extend beyond traditional marketing tactics.

The announcement also highlights the growing importance of Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO), emerging disciplines focused on improving visibility within AI-generated responses rather than conventional search engine rankings alone. As AI assistants become more integrated into business workflows, marketers are increasingly investing in strategies designed to influence how these systems discover, interpret, and cite brand information.

For both firms, the partnership represents an effort to help organizations adapt to a future where market visibility is determined not only by what companies publish themselves, but also by how effectively they earn trust across the broader information ecosystem.

As AI-mediated discovery continues to reshape enterprise buying behavior, organizations that successfully combine authoritative content, earned media presence, strategic communications, and digital trust signals may gain a significant advantage in the increasingly competitive battle for buyer attention.

Market Landscape

AI-powered search and discovery platforms are rapidly changing how B2B buyers research vendors and make purchasing decisions. Traditional SEO remains important, but marketers are increasingly investing in Answer Engine Optimization (AEO), Generative Engine Optimization (GEO), digital authority building, and earned media strategies to influence visibility within AI-generated responses.

Research from Gartner, Forrester, and industry analysts indicates that buyers are conducting more independent research than ever before, often consulting AI assistants before engaging with vendors directly. This shift is driving greater demand for integrated strategies that combine public relations, content marketing, search optimization, analyst relations, and demand generation into a unified trust-building framework.

Top Insights

• Plat4orm and Edge Marketing have partnered to help organizations improve visibility across AI-powered search and discovery environments.
• The Trusted Answer Growth System™ combines communications, earned media, content strategy, AEO, and demand generation into a unified visibility framework.
• AI platforms such as ChatGPT, Claude, and Gemini are increasingly influencing how B2B buyers research and evaluate vendors.
• Third-party validation, media coverage, analyst commentary, and authoritative content are becoming critical trust signals in AI-generated answers.
• Organizations in regulated and complex industries are increasingly investing in strategies that strengthen digital credibility and authority.

Get in touch with our MarTech Experts