The customer experience market is entering a new phase where enterprises are moving beyond isolated AI pilots and toward integrated operational deployments. That shift is driving new alliances between business process outsourcing providers and enterprise AI vendors, as companies look for ways to combine automation with human-led service delivery at scale.

Against that backdrop, Atento and Cresta announced a multi-year strategic partnership focused on hybrid human-AI customer experience solutions across the United States and Latin America. The agreement combines Atento’s CX management and outsourcing infrastructure with Cresta’s conversational AI platform to help enterprises deploy AI agents alongside human customer service teams.

The partnership reflects a broader trend reshaping the customer experience management market: enterprises increasingly want AI systems that operate inside existing workflows rather than standalone automation tools that create operational silos.

Atento said Cresta’s customer experience AI platform will become part of its Atent.AI offering, allowing clients to deploy AI-assisted customer support models that combine automated interactions, real-time agent assistance, and conversation intelligence. The companies are positioning the joint solution as a unified operational layer for enterprise contact centers rather than a narrow chatbot deployment.

The announcement comes as enterprise demand for AI-enabled CX infrastructure continues to accelerate. According to Gartner, generative AI is expected to influence the majority of customer service interactions over the next several years, while McKinsey & Company has estimated that AI-powered automation could significantly reduce customer care operating costs while improving response consistency and personalization.

For enterprise marketing and customer experience teams, the strategic value lies in operational integration. Many organizations already use fragmented stacks involving CRM platforms, marketing automation systems, customer data platforms, and separate AI applications. The challenge has shifted from adopting AI to orchestrating it across enterprise workflows.

That is where partnerships like this are gaining traction.

Cresta has built its platform around AI-assisted customer conversations, including real-time coaching for agents, automated quality monitoring, and AI-generated customer insights. The company competes in an increasingly crowded CX AI market that includes platforms from Salesforce, Microsoft, Google Cloud, and Amazon Web Services, all of which are investing heavily in conversational AI and contact center automation.

Unlike many software vendors, however, Cresta is pairing its technology with a large-scale outsourcing and CX operations provider. That distinction matters because enterprises deploying AI in customer service environments often struggle with implementation complexity, workforce adaptation, governance, and multilingual support.

Atento operates across multiple international markets and has deep operational exposure in Latin America, where AI-enabled customer service transformation is accelerating but remains uneven across industries. The partnership could give Cresta broader access to enterprise clients seeking managed AI deployments rather than standalone software procurement.

The companies said the integrated model will support AI agents, AI-augmented human agents, and enterprise conversation intelligence within a single architecture. In practice, that means routine inquiries can be automated while human agents receive live guidance and analytics during more complex customer interactions.

The concept of a “hybrid workforce” is becoming central to modern CX infrastructure strategies. Instead of replacing agents outright, enterprises are increasingly using AI to reduce handling time, improve compliance, surface customer intent signals, and assist agents during conversations.

That operational model aligns with broader enterprise software trends. Platforms across the martech and enterprise SaaS ecosystem are increasingly converging around unified intelligence layers that connect customer data, automation, analytics, and AI decision-making.

For marketers, this evolution has implications beyond customer support.

Customer conversations generate high-value first-party data that can influence audience segmentation, retention strategies, personalization, and predictive analytics. As AI platforms become more deeply integrated into CX workflows, customer service operations are becoming a more important source of actionable marketing intelligence.

The partnership also signals continued momentum in Latin America’s enterprise AI market, which has become an emerging growth region for CX modernization. Businesses operating across multilingual customer environments are under increasing pressure to improve automation capabilities without sacrificing service quality or regulatory compliance.

Industry analysts have noted that enterprises are becoming more selective about AI investments after an initial wave of experimentation. Rather than deploying multiple disconnected AI applications, organizations are prioritizing platforms that integrate directly into business operations and deliver measurable productivity gains.

Atento CEO Dimitrius Oliveira described the partnership as a response to changing enterprise expectations around AI deployment, while Cresta CEO Ping Wu emphasized the need for operational scale and unified AI-human collaboration.

The broader competitive landscape suggests more partnerships of this type are likely ahead. As enterprise buyers push for operational AI rather than experimental deployments, technology vendors and outsourcing providers are increasingly aligning to deliver integrated customer experience transformation services.

For the CX industry, the shift may redefine how enterprises evaluate AI adoption — not simply as a software purchase, but as a long-term operational strategy tied to workforce design, automation governance, and customer engagement infrastructure.

Market Landscape

The global customer experience AI market is becoming increasingly competitive as enterprises accelerate investments in conversational AI, contact center automation, and AI-powered analytics. Major enterprise platforms including Adobe, Salesforce, and Microsoft Dynamics 365 are embedding generative AI capabilities directly into CRM and customer engagement platforms.

Research from IDC indicates that worldwide AI software spending continues to rise sharply as enterprises prioritize operational automation and intelligent workflow orchestration. In parallel, BPO and CX outsourcing providers are evolving into AI transformation partners rather than traditional call center operators.

The Atento-Cresta partnership reflects this convergence between enterprise AI software and operational service delivery.

Top Insights

• Atento and Cresta are combining enterprise CX outsourcing infrastructure with conversational AI technology to create hybrid human-AI customer service operations across the U.S. and Latin America.
• The partnership focuses on operational AI deployment rather than isolated automation pilots, integrating AI agents, live agent assistance, and conversation intelligence into unified CX workflows.
• Enterprises are increasingly seeking AI platforms that integrate with existing CRM, marketing automation, and customer engagement systems instead of fragmented standalone AI tools.
• The agreement highlights growing demand for multilingual, enterprise-scale AI customer support solutions, particularly in Latin American markets undergoing digital transformation.
• Hybrid workforce models are emerging as a dominant enterprise CX strategy, allowing businesses to automate repetitive interactions while augmenting human agents with real-time intelligence.

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Healthcare organizations are facing growing pressure to modernize patient engagement, strengthen digital brand positioning, and compete in an increasingly crowded care delivery market. That shift is driving demand for specialized healthcare marketing and growth advisory firms capable of combining strategic communications, data-driven marketing, and healthcare industry expertise.

Against that backdrop, Sage Growth Partners has named Kenneth "Boh" Hatter as President and Head of Marketing, expanding his leadership role as the firm accelerates national growth initiatives.

The appointment signals Sage’s continued focus on healthcare growth strategy as hospitals, health systems, digital health companies, and care providers increase investments in marketing transformation, patient acquisition, and healthcare consumer engagement.

Hatter brings more than three decades of experience across healthcare marketing, strategic communications, advertising, and brand development. He previously served as Chief Marketing Officer at Sage and has been part of the company’s ownership group since 2011.

In his expanded role, Hatter will oversee strategic growth initiatives, executive client relationships, and the firm’s broader marketing practice. The move comes as healthcare organizations continue adapting to changing patient expectations, rising competition from retail healthcare entrants, and growing digital engagement demands.

The healthcare marketing sector has evolved significantly over the past decade. Health systems are no longer relying solely on traditional referral models or localized brand awareness campaigns. Instead, providers are increasingly adopting enterprise marketing technologies, customer relationship management platforms, predictive analytics, and omnichannel engagement strategies similar to those used in retail and consumer industries.

That transition has created new opportunities for healthcare-focused marketing firms.

According to McKinsey & Company, healthcare consumers increasingly expect personalized digital experiences, streamlined communication, and transparent service interactions. At the same time, research from Gartner suggests healthcare organizations are expanding investments in digital marketing infrastructure, automation, and customer experience technologies to improve patient acquisition and retention.

Sage Growth Partners operates within that evolving intersection of healthcare strategy and enterprise marketing transformation.

Before joining Sage, Hatter founded Hatter Communications, a Maryland-based advertising and public relations consultancy recognized by AdWeek as one of the country’s leading small agencies. Earlier in his career, he served as vice president and chief marketing officer at USF&G, where he helped launch the USF&G Sugar Bowl sponsorship, widely recognized as an early example of large-scale corporate sports sponsorship integration.

His career portfolio spans work with Fortune 50 companies and organizations including the American Red Cross, Coca-Cola, BASF, ABC Sports, and Bon Secours Health System.

The healthcare marketing industry itself is becoming increasingly technology-driven. Modern healthcare growth strategies now incorporate marketing automation, AI-powered patient engagement, customer data platforms, CRM integrations, and digital analytics to manage patient journeys more effectively.

Major enterprise technology vendors including Salesforce Health Cloud, Adobe Experience Cloud, and Microsoft Cloud for Healthcare continue expanding healthcare-specific marketing and customer engagement capabilities as providers seek more integrated digital infrastructure.

For healthcare organizations, leadership appointments like this reflect a broader strategic priority: aligning marketing, communications, and growth operations with enterprise digital transformation initiatives.

Healthcare systems are increasingly competing on brand experience, digital accessibility, patient retention, and consumer trust. That means marketing leaders are playing a larger operational role across healthcare enterprises, particularly as AI, analytics, and personalization technologies reshape patient engagement models.

Sage CEO Dan D'Orazio described Hatter as a strategic leader capable of scaling teams and driving measurable business outcomes. Hatter, meanwhile, framed the company’s next phase around insight-driven growth and innovation within healthcare marketing.

The timing is notable.

Healthcare organizations continue navigating workforce shortages, rising operational costs, evolving reimbursement models, and growing competition from digital-first healthcare platforms. As a result, strategic marketing and growth consulting firms are becoming more closely tied to enterprise transformation efforts rather than functioning solely as external branding partners.

Industry analysts expect that convergence between healthcare operations, marketing technology, and AI-driven engagement platforms to continue accelerating over the next several years.

For firms like Sage Growth Partners, executive leadership expansion may reflect not only company growth, but also the increasing importance of specialized healthcare marketing expertise in a digital-first healthcare economy.

Market Landscape

The healthcare marketing and patient engagement sector is undergoing rapid modernization as providers invest in digital transformation, omnichannel communication, and AI-enabled engagement strategies. Enterprise healthcare organizations are increasingly adopting CRM systems, customer data platforms, predictive analytics, and marketing automation technologies to improve patient acquisition and retention.

Research from IDC indicates healthcare organizations are expanding spending on digital engagement technologies as patient expectations continue shifting toward consumer-grade digital experiences.

At the same time, healthcare providers face mounting competitive pressure from retail health brands, telehealth platforms, and digitally native care delivery companies. That environment is driving demand for healthcare-focused growth strategy firms capable of integrating marketing, communications, analytics, and digital infrastructure.

Top Insights

• Sage Growth Partners promoted healthcare marketing veteran Boh Hatter to President as healthcare organizations accelerate investments in digital engagement and enterprise growth strategies.
• Hatter brings more than 30 years of experience spanning healthcare communications, strategic branding, enterprise marketing, and large-scale consumer engagement initiatives.
• Healthcare marketing firms are increasingly evolving into digital transformation advisors as providers adopt AI, CRM platforms, and omnichannel patient engagement technologies.
• The appointment reflects growing enterprise demand for healthcare-specific marketing expertise tied to patient acquisition, retention, and digital brand differentiation.
• Healthcare organizations are expanding investments in data-driven marketing infrastructure to compete with digital-first healthcare and retail health platforms.

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The race to operationalize AI across enterprise data platforms is accelerating beyond traditional SaaS categories and into infrastructure-heavy industries like renewable energy, power markets, and data center development. Companies managing large proprietary datasets are increasingly embedding generative AI tools directly into research and workflow systems rather than offering standalone automation features.

That trend is now reaching the energy intelligence sector.

New Project Media announced the launch of “NPM Edge AI,” a new artificial intelligence layer integrated across its global intelligence platform covering renewable energy, power infrastructure, and data center markets.

The rollout reflects a broader shift in how infrastructure investors, developers, and advisory firms are consuming market intelligence. Instead of relying on static databases or manual research processes, enterprise users are increasingly demanding AI-powered systems capable of synthesizing fragmented data, generating strategic analysis, and accelerating investment decision-making.

NPM said the new AI functionality is trained and informed by more than six years of proprietary intelligence and project data accumulated across its platform. The company tracks more than 100,000 infrastructure and energy-related projects globally, creating a large domain-specific dataset that can be used to support AI-driven market analysis.

The platform is aimed at developers, investors, infrastructure advisors, corporate strategy teams, and energy market participants seeking faster access to actionable insights tied to project development, power constraints, interconnection activity, and capital deployment opportunities.

The move places NPM within a growing category of vertical AI intelligence providers — companies embedding generative AI into industry-specific data ecosystems rather than building general-purpose AI applications.

That distinction matters in sectors like renewable energy and infrastructure development, where domain expertise and proprietary datasets often determine the quality of decision-making outputs.

According to McKinsey & Company, infrastructure and energy organizations are increasingly adopting AI to optimize investment modeling, operational forecasting, and project planning. Meanwhile, Gartner has identified domain-specific AI applications as one of the fastest-growing enterprise software segments, particularly in industries dependent on large-scale operational datasets.

NPM Edge AI is designed to move beyond basic keyword search functionality. The company said users can generate AI-assisted company research, analyze filings and market documents, evaluate power purchase agreement trends, identify project bottlenecks, and assess development efficiency across regions and operators.

One of the platform’s more notable use cases involves interconnection queue analysis — an increasingly important issue in renewable energy development as grid congestion and transmission bottlenecks delay project approvals across North America and other global markets.

In practical terms, the AI layer enables infrastructure market participants to ask complex sector-specific questions using natural language prompts while grounding responses in NPM’s proprietary intelligence environment.

That approach mirrors broader enterprise AI strategies emerging across sectors including financial services, martech, healthcare, and enterprise analytics. Rather than replacing existing software infrastructure, companies are embedding AI into operational workflows to improve productivity and accelerate insight generation.

The infrastructure intelligence market itself is becoming increasingly competitive as investors seek faster visibility into power availability, data center expansion, transmission constraints, and renewable project economics.

Major enterprise cloud providers including Microsoft Azure AI, Google Cloud AI, and Amazon Web Services AI Services continue expanding AI capabilities for enterprise analytics and data orchestration. At the same time, specialized intelligence firms are differentiating themselves through proprietary datasets and vertical expertise.

NPM founder and CEO Ken Meehan described the launch as the next phase of the company’s evolution from reporting and market intelligence into AI-assisted infrastructure analysis.

His comments reflect a growing industry view that generative AI systems become more valuable when paired with proprietary enterprise data rather than relying solely on public web information.

That dynamic is especially relevant in energy and infrastructure markets, where access to differentiated intelligence can directly influence investment timing, development strategy, and competitive positioning.

For enterprise users, the value proposition centers on reducing manual research workloads and improving speed-to-decision. The company said users can evaluate development concentrations, identify projects facing likely delays, and prioritize investment or business development opportunities more efficiently.

The launch also underscores the increasing overlap between AI infrastructure and physical infrastructure markets.

As hyperscale cloud providers and AI companies continue expanding global compute capacity, demand for energy generation, transmission access, and data center infrastructure has intensified. That convergence is turning energy intelligence platforms into increasingly strategic tools for institutional investors, utilities, and digital infrastructure operators.

Industry analysts expect the next wave of enterprise AI adoption to focus less on generalized experimentation and more on workflow-integrated intelligence systems capable of delivering measurable operational advantages.

For New Project Media, the launch positions the company within that evolving enterprise AI landscape — one where proprietary data ecosystems may become just as important as the AI models themselves.

Market Landscape

The global market for AI-powered infrastructure intelligence is expanding as renewable energy developers, institutional investors, utilities, and data center operators seek faster access to actionable operational data. Energy transition projects, grid modernization, and AI-driven compute demand are increasing the complexity of infrastructure planning and capital allocation.

Research from IDC suggests enterprise spending on AI-enabled analytics platforms continues to accelerate across industrial and infrastructure sectors. At the same time, energy markets are facing mounting pressure from transmission congestion, permitting delays, and rapidly rising data center electricity demand.

Industry platforms that combine proprietary infrastructure datasets with AI-powered analysis are emerging as a strategic differentiator for investors and project developers navigating increasingly competitive markets.

Top Insights

• New Project Media launched NPM Edge AI, integrating generative AI into its renewable energy, power, and data center intelligence platform powered by proprietary infrastructure datasets.
• The platform enables investors and developers to analyze projects, interconnection risks, PPA pricing trends, and infrastructure bottlenecks using AI-driven natural language workflows.
• Enterprise demand for vertical AI intelligence platforms is rising as infrastructure markets become more data-intensive and operationally complex.
• AI adoption in renewable energy and data center development is shifting toward workflow-integrated analytics rather than standalone automation tools or generalized AI assistants.
• Proprietary industry datasets are becoming increasingly important as enterprises seek differentiated AI-driven intelligence for capital deployment and strategic planning decisions.

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Artificial intelligence adoption inside enterprise finance departments is moving beyond experimentation and into operational deployment. While many enterprises have tested generative AI pilots over the past two years, relatively few have integrated AI deeply into core financial workflows such as forecasting, cash flow management, accounts payable, and financial planning.

That gap is creating a new battleground for enterprise technology providers and consulting firms seeking to operationalize “agentic AI” inside the Office of the CFO.

Genpact announced an expanded alliance with Google Cloud focused on building and scaling AI-driven finance solutions designed specifically for enterprise CFO organizations.

The partnership centers on the deployment of specialized AI agents built on Google Cloud infrastructure and distributed through Google Cloud’s Agent Marketplace. The companies said the goal is to help enterprises modernize finance operations while turning AI investments into measurable operational outcomes.

The announcement reflects a broader enterprise shift toward agentic AI — systems capable of autonomously executing tasks, interacting with enterprise applications, learning from workflows, and supporting decision-making processes with limited human intervention.

Unlike traditional generative AI chat interfaces, agentic AI platforms are designed to function inside operational systems, automating repetitive work while coordinating across enterprise datasets, analytics tools, and business applications.

Genpact’s first offering under the expanded alliance, called “Finance One – Revenue Lens Agents,” is aimed at helping CFO organizations improve revenue forecasting accuracy, optimize cash flow visibility, and automate elements of financial analysis.

The company said additional AI agents targeting accounts payable, record-to-report workflows, and financial planning and analysis are planned as part of a broader finance transformation strategy.

The Office of the CFO has become one of the fastest-growing enterprise AI opportunity areas as organizations seek to improve operational efficiency amid economic uncertainty, regulatory pressure, and increasingly complex financial environments.

According to Gartner, CFOs are accelerating investments in AI-enabled automation and predictive analytics as finance teams face growing pressure to deliver faster insights with leaner operational structures. Research from McKinsey & Company also suggests that AI adoption in finance operations could significantly improve productivity while reducing manual processing costs across accounting and reporting workflows.

For enterprise finance leaders, the challenge is no longer simply adopting AI tools — it is integrating AI into production environments while maintaining governance, compliance, data security, and operational reliability.

That is where alliances between enterprise cloud providers and domain-focused consulting firms are becoming increasingly important.

Google Cloud has been aggressively expanding its enterprise AI ecosystem, positioning its infrastructure and AI services as foundational layers for generative and agentic AI deployments. The company’s Agent Marketplace strategy is designed to accelerate adoption by giving enterprises direct access to industry-specific AI applications that integrate into existing cloud environments.

Genpact, meanwhile, brings process engineering and operational expertise across finance, accounting, analytics, and enterprise transformation services.

The partnership combines those capabilities at a time when enterprises are looking for production-ready AI systems rather than standalone experimental tools.

Kevin Ichhpurani, President of Google Cloud’s Global Partner Ecosystem, framed the alliance around scalable enterprise AI deployment, emphasizing the need for domain-specific operational context. Genpact Global Agentic AI Officer Vijay Vijayasankar described the current disconnect between AI pilots and production-scale finance transformation as a central problem the companies are attempting to solve.

The finance technology market is becoming increasingly competitive as enterprise vendors race to embed AI into ERP systems, analytics platforms, and operational finance software.

Major enterprise software providers including SAP, Oracle, Microsoft Dynamics 365, and Salesforce are all expanding AI-driven automation and analytics capabilities aimed at finance organizations.

The emergence of agent marketplaces and specialized AI agents suggests the next phase of enterprise AI competition may focus less on generalized AI assistants and more on workflow-specific operational intelligence.

Genpact said the expanded alliance is already supporting large enterprise modernization initiatives, including finance and analytics transformation projects within healthcare, retail, and pharmaceutical organizations.

That cross-industry applicability is important because finance modernization has become a board-level priority across sectors facing tighter margins, evolving compliance requirements, and increasing demand for real-time operational visibility.

For enterprise marketing and technology leaders, the trend also signals growing convergence between AI infrastructure, enterprise SaaS ecosystems, and operational business functions.

As organizations embed AI agents into finance systems, customer operations, supply chains, and analytics environments, the role of enterprise AI is evolving from productivity enhancement toward autonomous workflow orchestration.

Industry analysts expect that evolution to accelerate as enterprises mature their AI governance frameworks and seek measurable returns on AI investments.

The Genpact-Google Cloud alliance reflects that broader transition — one where enterprise AI is increasingly evaluated not by pilot adoption rates, but by operational impact inside critical business functions.

Market Landscape

The enterprise finance automation market is rapidly evolving as organizations deploy AI-powered analytics, forecasting, and workflow orchestration tools to modernize CFO operations. Finance departments are increasingly adopting generative AI and agentic AI systems to reduce manual processing, improve forecasting accuracy, and accelerate financial decision-making.

Research from IDC indicates enterprise AI spending continues to grow sharply across finance and operations functions, particularly in areas involving predictive analytics, intelligent automation, and workflow optimization.

Cloud hyperscalers and enterprise SaaS vendors are now competing to establish AI ecosystems that combine infrastructure, data orchestration, and industry-specific operational intelligence.

Top Insights

• Genpact and Google Cloud expanded their alliance to deliver agentic AI solutions designed specifically for enterprise finance and Office of the CFO operations.
• The partnership introduces specialized AI agents capable of automating forecasting, cash flow analysis, accounts payable, and financial planning workflows.
• Enterprises are increasingly shifting from experimental AI pilots toward production-ready operational AI systems integrated into finance infrastructure.
• Google Cloud’s Agent Marketplace is emerging as a distribution channel for industry-specific AI applications embedded within enterprise cloud environments.
• Agentic AI is becoming a major enterprise software trend as organizations seek autonomous workflow execution and real-time operational intelligence.

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Event technology platforms are increasingly moving beyond basic badge scanning and toward AI-driven intelligence systems capable of transforming live event interactions into structured customer data. As enterprise marketing teams face growing pressure to prove event ROI and accelerate post-event engagement, vendors are embedding automation, conversational AI, and data enrichment directly into event workflows.

That shift is driving a new wave of innovation in the event martech sector.

Captello has launched a new “Intelligent Scanner” platform designed to capture and enrich event data using AI-powered automation and real-time data processing.

The company says the scanner enables users to collect information from event badges, business cards, QR codes, paper documents, handwritten notes, LinkedIn profiles, and live conversations through a single workflow interface. The launch reflects broader demand for unified event intelligence systems that reduce manual data entry and improve lead qualification accuracy during in-person events.

For B2B marketing teams, the challenge surrounding event lead capture has become increasingly complex. Enterprise organizations now participate across trade shows, conferences, partner summits, and networking events where attendee data is often fragmented across registration systems, disconnected scanning tools, and manual note-taking processes.

Captello is positioning the Intelligent Scanner as an AI-driven alternative to traditional lead retrieval systems that depend heavily on event-specific integrations or barcode infrastructure.

The platform’s core differentiator appears to be its multi-source capture approach combined with AI-powered data enrichment. According to the company, scanned data is processed through a layered AI engine capable of pulling contact details, company information, and related business data from more than 25 external sources.

That functionality aligns with a broader enterprise trend toward real-time data enrichment and automated CRM synchronization across sales and marketing workflows.

According to Gartner, organizations are increasingly prioritizing first-party data capture and workflow automation as cookie deprecation and privacy regulations reshape customer acquisition strategies. Meanwhile, Forrester has noted that event marketing remains a critical B2B demand generation channel despite rising investments in digital engagement platforms.

Captello’s scanner also introduces conversation intelligence capabilities, allowing users to record and transcribe consent-based event conversations. The platform can reportedly generate transcripts, identify speakers, surface action items, and recommend follow-up actions before automatically routing the information into CRM and marketing automation systems.

The addition of conversational AI reflects the growing overlap between event technology and broader enterprise AI infrastructure.

Sales and marketing organizations increasingly want event interactions to function as structured data sources rather than isolated networking moments. By integrating conversation summaries and AI-generated recommendations directly into CRM workflows, vendors are attempting to shorten sales cycles and improve lead follow-up efficiency.

Captello said the platform integrates with more than 6,000 CRM and marketing automation systems and over 300 registration providers. That interoperability is becoming increasingly important as enterprise martech stacks grow more fragmented.

Large enterprises commonly operate across multiple customer data platforms, sales engagement tools, event management systems, and marketing automation platforms including Salesforce, HubSpot, Adobe Marketo Engage, and Microsoft Dynamics 365. Event technology vendors are increasingly expected to integrate seamlessly into those ecosystems rather than operate as standalone tools.

The launch also highlights how AI is reshaping physical event engagement at a time when in-person marketing is regaining momentum following several years of hybrid and virtual event experimentation.

While virtual event adoption surged during the pandemic, many B2B organizations have returned to in-person conferences and industry events as critical channels for pipeline generation and relationship development. That resurgence has renewed focus on event attribution, lead intelligence, and measurable engagement outcomes.

Captello CEO Ryan Schefke described the scanner as a way to simplify real-time lead capture while preserving data quality and operational efficiency. CTO Nassir Jamal emphasized the AI enrichment layer as a central part of the platform’s value proposition.

The broader event technology market is becoming increasingly competitive as vendors integrate AI across networking, analytics, meeting management, and event automation systems.

Companies are racing to differentiate themselves through workflow intelligence, predictive analytics, and automated follow-up capabilities rather than basic registration or scanning functionality alone.

For enterprise marketers, that evolution reflects a larger industry shift: events are no longer treated as isolated brand awareness activities, but as data-rich customer acquisition channels tightly connected to CRM systems, sales operations, and revenue attribution models.

Industry analysts expect AI-driven event intelligence platforms to become increasingly central to enterprise demand generation strategies as organizations seek more measurable and scalable approaches to live engagement.

For Captello, the Intelligent Scanner positions the company within that next phase of event technology — one where AI-powered data orchestration may become just as important as attendee engagement itself.

Market Landscape

The global event technology market is undergoing rapid transformation as enterprises invest in AI-powered engagement tools, automated lead capture systems, and real-time analytics platforms. Event organizers and B2B marketing teams are increasingly seeking integrated solutions capable of connecting in-person interactions directly to CRM, sales enablement, and marketing automation workflows.

Research from IDC suggests enterprise spending on AI-enabled customer engagement technologies continues to rise as organizations prioritize first-party data collection and measurable event ROI.

At the same time, growing privacy regulations and the decline of third-party tracking are increasing the strategic importance of direct lead capture and enriched customer intelligence generated during live events.

Top Insights

• Captello launched an AI-powered Intelligent Scanner designed to capture and enrich event data from badges, conversations, business cards, and documents in real time.
• The platform combines AI-driven lead enrichment, conversation intelligence, and CRM automation to streamline post-event sales and marketing workflows.
• Event technology platforms are evolving beyond badge scanning toward integrated customer intelligence systems connected directly to enterprise martech stacks.
• AI-powered event data orchestration is becoming increasingly important as enterprises prioritize first-party customer data and measurable event ROI.
• Seamless integrations with CRM and marketing automation platforms are emerging as a key differentiator in the competitive event technology market.

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Customer relationship management platforms are increasingly evolving into unified engagement ecosystems as small and mid-sized businesses push back against fragmented sales and marketing software stacks. The latest battleground in the CRM market is inbound engagement — specifically, how companies capture, qualify, and convert website visitors without relying on disconnected third-party tools.

Nimble CRM is the latest vendor attempting to simplify that process with the launch of Nimble Web Chat, a native live chat and inbound lead capture system integrated directly into its CRM platform.

The new product enables businesses to engage website visitors in real time while automatically creating CRM contact records and logging conversations inside customer timelines. Nimble is bundling the feature with its Web Forms offering for a flat $12 monthly company-wide fee, regardless of team size — a pricing model that contrasts sharply with enterprise CRM vendors that often charge on a per-user basis.

The launch reflects broader shifts taking place across the CRM and martech landscape as smaller organizations seek alternatives to increasingly complex enterprise software ecosystems.

For many SMBs, customer engagement workflows are spread across multiple disconnected tools including live chat platforms, marketing automation systems, CRMs, data connectors, and email engagement software. That fragmentation can create operational inefficiencies, inconsistent customer data, and higher software costs.

Nimble founder and CEO Jon Ferrara framed the launch as a response to those challenges, arguing that smaller businesses have historically faced a difficult choice between stitching together standalone applications or adopting expensive enterprise-grade marketing platforms requiring significant implementation resources.

The new Web Chat product is designed primarily for high-intent conversion environments such as pricing pages, campaign landing pages, and service pages where visitor engagement is more likely to translate into qualified pipeline opportunities.

When visitors initiate a conversation, the platform automatically notifies assigned team members across desktop and mobile channels. Each interaction is tied directly to a CRM profile, allowing businesses to maintain a unified relationship history that includes email engagement, sequences, sales pipeline activity, and chat interactions.

That integrated approach aligns with broader enterprise trends toward consolidated customer engagement infrastructure.

According to Gartner, organizations are increasingly prioritizing unified customer data environments as businesses attempt to reduce martech complexity and improve cross-channel personalization. Research from Forrester has similarly highlighted the growing importance of conversational engagement tools as part of modern customer experience strategies.

Nimble’s launch also underscores the growing role of AI within SMB-focused CRM platforms.

The platform includes an “AI Chat Helper” feature designed to engage visitors automatically when live representatives are unavailable. The AI assistant can ask qualifying questions, capture lead details, generate conversation summaries, and provide context for follow-up workflows.

AI-powered conversational engagement is becoming a major area of investment across the CRM industry as vendors race to integrate generative AI into sales, customer support, and marketing operations.

Major platforms including Salesforce, HubSpot, Microsoft Dynamics 365, and Zoho CRM have all expanded AI-powered automation capabilities over the past year, ranging from predictive lead scoring to generative content creation and conversational AI assistants.

Nimble’s positioning, however, appears focused less on enterprise-scale orchestration and more on affordability and operational simplicity for smaller businesses.

The pricing strategy may prove significant in a market where many SMBs are reevaluating software costs amid rising subscription complexity. Rather than charging per seat, Nimble is packaging inbound engagement tools at a flat company-wide rate, including a shared allocation of forms and chat capture points.

The company said early beta users reported faster lead response times and smoother transitions from website engagement to CRM follow-up workflows.

The launch is also part of a broader expansion of Nimble’s native sales and email marketing stack, which now includes email marketing tools, group messaging, automated sequences, AI-generated email templates, and multi-sender campaign attribution.

That expansion reflects a wider market trend where CRM vendors are attempting to evolve into all-in-one customer engagement platforms rather than serving solely as contact databases or sales tracking systems.

For enterprise marketers and sales teams, the larger industry implication is clear: CRM platforms are increasingly becoming operational hubs that connect inbound capture, outbound engagement, automation, analytics, and AI-driven personalization within a single customer record.

Industry analysts expect the CRM market to continue consolidating around unified engagement ecosystems as businesses seek fewer tools, tighter integrations, and more centralized customer intelligence.

For Nimble, the introduction of Web Chat represents another step toward competing not just as a CRM provider, but as a broader relationship engagement platform designed to simplify customer acquisition and lifecycle management for growing businesses.

Market Landscape

The CRM and customer engagement software market is rapidly evolving as businesses seek integrated platforms capable of managing customer acquisition, communication, automation, and analytics from a unified system. AI-powered conversational engagement tools are becoming increasingly central to modern sales and marketing workflows.

Research from IDC suggests organizations are accelerating investments in AI-enabled CRM technologies to improve customer responsiveness, reduce manual processes, and unify fragmented customer data environments.

At the same time, SMBs are increasingly prioritizing software simplicity and pricing transparency as enterprise SaaS ecosystems become more operationally complex and expensive.

Top Insights

• Nimble CRM launched Web Chat, adding AI-powered live website engagement directly into its customer relationship management platform.
• The platform automatically creates CRM contacts and logs conversations, helping businesses unify inbound engagement and customer relationship data.
• AI Chat Helper enables automated lead qualification and conversation summaries when human representatives are unavailable.
• The launch reflects growing demand for consolidated CRM and customer engagement platforms that reduce reliance on disconnected third-party tools.
• SMB-focused CRM vendors are increasingly competing on affordability, operational simplicity, and integrated AI-powered workflows.

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The mobile advertising market is rapidly shifting toward AI-powered optimization as app publishers and marketers face increasing pressure to acquire users more efficiently within increasingly restricted mobile ecosystems. Apple’s privacy framework changes, rising acquisition costs, and intensifying competition inside app marketplaces have pushed advertisers toward data-driven app growth platforms capable of combining analytics, automation, and AI-powered campaign intelligence.

Against that backdrop, InMobi has acquired MobileAction, an AI-powered app growth and analytics platform focused heavily on the iOS ecosystem.

Financial terms of the deal were not disclosed.

The acquisition strengthens InMobi’s position within the rapidly evolving app advertising and agentic commerce landscape, while adding specialized expertise in Apple Ads optimization and App Store Optimization (ASO) — two increasingly critical areas for mobile marketers navigating Apple’s tightly controlled ecosystem.

Founded in 2013 and headquartered in San Francisco, MobileAction has built a significant presence in mobile app intelligence and performance marketing. The platform is widely used by global app publishers and brands to improve app discoverability, analyze competitive positioning, and optimize user acquisition strategies across Apple’s App Store.

The company says its datasets span more than 90 million ad creatives, 6 million keywords, 5 million apps, 100,000 publishers, and 500,000 advertisers, providing a substantial intelligence layer for AI-powered app marketing optimization.

The acquisition reflects a broader trend reshaping the mobile advertising industry: the growing convergence between AI, app store intelligence, and automated advertising workflows.

As third-party tracking capabilities continue to decline following Apple’s App Tracking Transparency (ATT) changes, mobile marketers are increasingly relying on contextual targeting, first-party data strategies, predictive analytics, and AI-powered optimization systems to drive app growth.

According to Gartner, AI-driven advertising optimization and predictive audience modeling are becoming core priorities for mobile marketing organizations as privacy regulations reshape performance advertising infrastructure. Meanwhile, Forrester has identified app discoverability and AI-enhanced campaign automation as major growth areas within the mobile ad ecosystem.

MobileAction’s specialization in Apple Ads and App Store Optimization makes the acquisition particularly strategic for InMobi, which has been expanding beyond traditional mobile advertising into broader AI-powered commerce and consumer engagement infrastructure.

The company has increasingly positioned itself around “agentic commerce,” a concept describing AI-driven systems capable of automating customer discovery, personalization, recommendations, and advertising interactions across digital environments.

The acquisition also complements InMobi’s broader ecosystem strategy, which includes its Glance consumer platform and global advertising infrastructure.

By integrating MobileAction’s app intelligence capabilities, InMobi gains deeper visibility into app marketplace dynamics and user acquisition trends — both of which are becoming increasingly valuable as app marketing grows more competitive and algorithmically driven.

Rohit Dosi described the acquisition as a response to the advertising industry’s shift toward AI-led intelligence and platform-native expertise. MobileAction founder and CEO Aykut Karaalioglu emphasized the companies’ shared focus on AI-driven advertising innovation and data-informed decision-making.

The competitive landscape surrounding mobile app marketing has intensified significantly over the past several years.

Major technology platforms including Google Ads, Apple Search Ads, Meta Ads Manager, and TikTok for Business continue expanding AI-driven campaign automation capabilities as marketers seek more efficient ways to acquire and retain users.

At the same time, specialized mobile growth platforms are differentiating themselves through proprietary datasets, predictive analytics, and AI-enhanced optimization engines tailored specifically to app ecosystems.

The transaction also highlights the strategic importance of the iOS ecosystem within the broader mobile advertising economy.

Despite tighter privacy controls, Apple users remain highly valuable to advertisers because of higher engagement and spending patterns compared with many other mobile audiences. That has increased demand for platforms capable of improving visibility and conversion efficiency within Apple’s advertising and app discovery environment.

Following the acquisition, MobileAction will continue operating as a dedicated platform while joining the broader InMobi Group. The company’s teams across the United States, Europe, and Turkey will remain part of ongoing product development and global expansion efforts.

InMobi said it plans to continue investing in MobileAction’s product roadmap and go-to-market expansion across the United States, APAC, MENA, and other international markets.

For the broader adtech industry, the deal underscores how AI-powered intelligence platforms are becoming central to the future of app marketing. As mobile ecosystems become more privacy-centric and algorithmically complex, marketers increasingly need specialized AI systems capable of translating fragmented marketplace data into actionable growth strategies.

Industry analysts expect consolidation across mobile advertising, app intelligence, and AI optimization platforms to continue accelerating as companies compete to control the infrastructure layer behind next-generation mobile commerce and advertising experiences.

Market Landscape

The global mobile advertising and app intelligence market is undergoing rapid transformation as privacy regulations, AI-powered automation, and platform-native advertising ecosystems reshape user acquisition strategies. App publishers and marketers are increasingly investing in AI-driven optimization tools to improve discoverability, campaign efficiency, and customer retention.

Research from IDC indicates enterprise investments in AI-powered advertising analytics and automation continue to grow as marketers adapt to evolving privacy frameworks and rising acquisition costs.

The iOS advertising ecosystem has become especially competitive following Apple’s App Tracking Transparency changes, increasing demand for app store intelligence, contextual targeting, and predictive marketing technologies.

Top Insights

• InMobi acquired MobileAction to strengthen its AI-powered mobile advertising and app growth capabilities across the iOS ecosystem.
• MobileAction specializes in Apple Ads optimization and App Store Optimization, helping marketers improve app discoverability and acquisition efficiency.
• The acquisition reflects broader industry shifts toward AI-driven mobile advertising and platform-native optimization strategies following major privacy changes.
• AI-powered app intelligence platforms are becoming increasingly important as marketers seek alternatives to traditional third-party tracking infrastructure.
• InMobi is expanding its agentic commerce strategy by combining advertising infrastructure with AI-driven app growth and consumer engagement technologies.

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Financial institutions are confronting a growing compliance challenge: the explosion of digital communication channels, AI-generated content, and rising regulatory scrutiny is creating more data than human review teams can realistically manage. As firms adopt collaboration platforms, generative AI tools, and voice communications at scale, compliance departments are increasingly relying on artificial intelligence to identify meaningful risk signals hidden inside massive volumes of data.

That shift is accelerating demand for AI-powered compliance and supervision platforms.

Smarsh announced a new set of AI capabilities designed to reduce compliance “noise,” improve risk detection, and automate supervision workflows across regulated communications environments.

The company’s latest updates target one of the biggest operational pain points for regulated enterprises: the growing number of false positives generated by traditional compliance monitoring systems.

According to Smarsh, the new AI-powered Noise Reduction Agent can reduce false positives by more than 60%, helping compliance teams prioritize high-risk activity while cutting down manual review workloads. The company also introduced an AI Assistant for investigation support and a beta-stage Misconduct Detection Agent capable of identifying potential insider trading, market manipulation, secrecy patterns, harassment, and other compliance risks embedded within multilingual or jargon-heavy communications.

The launch reflects a broader trend reshaping the governance, risk, and compliance technology market.

Financial institutions, healthcare organizations, government agencies, and other regulated industries are under mounting pressure to supervise communications across email, collaboration platforms, messaging applications, voice systems, and increasingly, generative AI tools.

According to Gartner, enterprises are rapidly expanding investments in AI-powered governance and risk management systems as digital communication volumes continue to accelerate. Meanwhile, IDC has identified AI-driven compliance automation as one of the fastest-growing enterprise software segments within regulated industries.

Smarsh’s latest announcement suggests compliance vendors are increasingly positioning AI not merely as an automation tool, but as a filtering and intelligence layer capable of prioritizing actionable risks in real time.

That capability is becoming particularly important as firms adopt generative AI technologies internally.

The company announced new integrations for OpenAI ChatGPT Enterprise and Microsoft 365 Copilot, allowing enterprises to capture, archive, and supervise AI-generated conversations, prompts, and responses through compliant audit-ready workflows.

The integrations highlight a growing regulatory concern surrounding enterprise AI adoption: how organizations govern AI-generated communications while maintaining compliance with financial supervision and record-keeping requirements.

Regulators including FINRA and the U.S. Securities and Exchange Commission have increasingly emphasized digital communication oversight as firms adopt new collaboration and AI technologies.

The challenge for enterprises is scale.

Compliance teams often face millions of communications across messaging platforms, email systems, mobile channels, recorded calls, and AI-generated interactions. Traditional rule-based surveillance systems frequently generate excessive false positives, forcing teams to spend substantial time reviewing low-risk communications.

Smarsh’s AI enhancements are designed to address that operational inefficiency.

Within its Professional Archive platform, the company is embedding AI-driven summarization, contextual analysis, translation, and behavioral detection directly into investigation workflows. The goal is to help reviewers identify meaningful patterns faster while reducing manual investigative workloads.

The company is also expanding AI functionality within its voice compliance products.

Voice analytics has become a growing focus area for compliance technology providers as financial firms increasingly rely on recorded conversations across customer service, trading, and advisory environments. Smarsh said its updated Call Recording and Analytics platform includes AI-powered quality analysis, topic identification, risk prioritization, and advanced conversational detection capabilities designed to improve supervision of spoken interactions.

That reflects a broader industry trend toward multimodal compliance monitoring — combining text, voice, video, and AI-generated content into unified surveillance systems.

Major enterprise technology providers including Microsoft, Google Cloud, and Amazon Web Services are investing heavily in enterprise AI governance frameworks as customers seek secure methods for deploying generative AI inside regulated environments.

At the same time, specialized compliance vendors are differentiating themselves through domain-specific detection models, explainable AI outputs, and audit-ready workflows tailored to regulatory requirements.

Smarsh said customers using its AI systems have already reported measurable operational improvements, including a 20% increase in review capacity, more than 40 hours saved per reviewer each month, and significantly higher rates of risk identification.

For enterprise compliance leaders, the broader market shift is becoming increasingly clear: AI is no longer viewed solely as a productivity enhancement, but as a necessary operational layer for managing the growing complexity of digital communications governance.

Industry analysts expect regulatory oversight surrounding AI-generated communications and digital supervision to intensify over the next several years as organizations expand enterprise AI adoption across financial services and other highly regulated sectors.

For vendors like Smarsh, that creates a growing opportunity to position AI-powered compliance infrastructure as foundational technology for the next generation of regulated enterprise operations.

Market Landscape

The enterprise compliance and digital communications governance market is undergoing rapid transformation as organizations manage expanding volumes of messaging, collaboration, voice, and AI-generated communications. Financial institutions are under increasing pressure to modernize surveillance systems while maintaining compliance with evolving regulatory frameworks.

Research from Forrester suggests AI-powered governance and compliance automation is becoming a strategic investment priority for regulated enterprises seeking operational efficiency and improved risk visibility.

The rise of generative AI platforms has further intensified demand for compliant archiving, explainable AI supervision, and unified communication governance systems across enterprise environments.

Top Insights

• Smarsh introduced new AI-powered compliance tools designed to reduce false positives and improve risk detection across regulated communications environments.
• The company added integrations for ChatGPT Enterprise and Microsoft 365 Copilot to help firms supervise AI-generated communications and maintain audit-ready records.
• Financial institutions are increasingly adopting AI-powered surveillance platforms to manage growing communication volumes and regulatory complexity.
• AI-driven misconduct detection systems are becoming central to modern compliance workflows across messaging, email, and voice communication channels.
• Enterprise compliance technology is evolving toward multimodal supervision platforms capable of governing human and AI-generated interactions simultaneously.

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