• Adthena’s ChatGPT AdBridge simplifies migration by creating artificial intelligence (AI)-enriched keyword lists and negative keywords.
• The tool offers a free, practical entry point for advertisers to prepare campaigns for the ChatGPT Ads platform.

The launch of Adthena ChatGPT AdBridge is being touted as an industry-first, migration product designed to help agencies and brands prepare for ChatGPT Ads.

This free tool analyzes an advertiser’s Google Ads campaigns to create keyword lists and negative keywords ready for immediate upload directly into the new ChatGPT Ads platform. With ChatGPT Ads trial surpassing 600 advertisers and OpenAI expected to open the platform to all markets, Adthena is giving advertisers a practical head start, according to company officials.

How this is a First Step

Phillip Thune, CEO of Adthena, noted that ChatGPT Ads is the most significant new paid search channel in a generation, and the time to act is now.

“ChatGPT AdBridge turns our search intelligence into a free, practical tool that gets campaigns ready in minutes,” said Thune in a statement. “And for those who want to go further, our full ChatGPT Ads solution…will bring the same whole-market visibility that has made Adthena essential for Google paid search, applied to the world’s fastest growing new ad platform.”

How Integration Works

AdBridge connects to an advertiser’s Google Ads account via a simple integration that supplies both campaign structure and negative lists ready for immediate upload to ChatGPT Ads. The steps are:

• Connect to Google Ads account.
• Build ChatGPT Ads setup, as AI enriches campaigns, expands keyword coverage, condenses negatives, and maps intent categories.
• Download and export. Users will have two CSVs land in their inbox hat can be imported directly into ChatGPT Ads.
• Launch and go live. Download ready-to-submit keyword lists and paste directly into ChatGPT Ads.

Adthena will release its full ChatGPT Ads solution for trialists and early adopters, delivering a prompt market view alongside immediate optimization actions and search intelligence.

“You cannot ignore this new channel. We need to get ready, and this expansion will likely be funded from existing paid search budgets,” said Matthew Crawley at 7Stars, who recently joined Adthena’s Customer Advisory Board. “That makes AI search intelligence tools like Adthena’s critical, you need to know where to reallocate and where to invest. AdBridge gives our teams a fast, practical route to getting clients into ChatGPT Ads with confidence.”

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• G2 found 51% of B2B software buyers now start their research with AI chatbots, reshaping vendor selection and decision-making.
• AI chatbots are influencing buyer shortlists, with 83% of buyers feeling more confident in their final choice.

A new report from G2 highlights the impact that artificial intelligence (AI) is having with B2B software buyers.

G2’s The Answer Economy: How AI Search Is Rewiring B2B Software Buying report found that 51% of B2B software buyers now begin their purchasing process in an AI chatbot rather than a traditional search engine— and buyers increasingly return to AI chatbots at every stage of their journey.

The shift to AI chatbots as the starting point for software buying increases since G2’s last report, influencing vendor selection, and accelerating decisions— 69% of buyers indicated they chose a different software vendor than they initially planned based on AI chatbot guidance, and one-third purchased from a vendor they had never heard of before.

AI is Influencing Buyers Shortlists

G2 first began tracking this shift to AI search in its April 2025 Buyer Behavior Report. Now the trend shows no signs of plateauing as 83% report feeling more confident in their final choice with AI chatbots the top source influencing which vendors make buyer shortlists.

“We’re watching the third compression era of the buyer journey unfold in real time,” said Tim Sanders, Chief Innovation Officer at G2, in a statement. “The Yellow Pages compressed the market into the big book. Google compressed it into the first page of results. Now, AI chatbots are compressing it into a single answer.”

How B2B Buyers are Relying on AI Chatbots

The report, based on a March 2026 survey of 1,076 B2B software buyers and decision-makers, highlights how AI chatbots have accelerated software research, helping buyers achieve stronger outcomes. Nearly three in four (71%) B2B software buyers rely on AI chatbots for software research, compared to 60% previously. And 53% of B2B software buyers feel research done with an AI chatbot is more productive than traditional search, up from 36%.

In the answer economy, buyers have moved from reference to inference, leveraging AI to synthesize the research process and return a shortlist.

A third of respondents purchased from a vendor they weren’t familiar with. Eighty-five percent of buyers think more highly of a software vendor when an AI chatbot mentions them in a recommendation while four out of five buyers say AI chatbots accelerated their purchasing decision.

How Many Hours a Week Are AI Chatbots Being Used

G2 officials noted today’s software buyer is sophisticated as they increase their time with AI chatbots at work, running head-to-head comparisons, creating deep research reports, and using thinking mode for high-stakes evaluations. Other key finding of the report incldue:

• Nearly two-thirds of buyers now spend six or more hours per week using AI chatbots for work, and over 40% self-identify as power users who leverage them daily.
• Comparing vendor strengths and weaknesses is the top use case for AI chatbots in software research (41%) — ahead of basic product research, vendor identification, and use case validation.
• Forty-one percent of buyers use Deep Research tools regularly for software evaluations.
• ChatGPT remains the dominant AI chatbot for B2B software research (63%), but the competitive landscape is shifting fast.

“Buyers have moved from reference to inference. Instead of gathering sources and synthesizing the data themselves, they trust AI chatbots to return the shortlist in a single prompt. That disrupts how software vendors need to think about their presence,” said Sanders.

Click here for the full report.

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• Conductor’s AgentStack enables brands to scale AI-driven search visibility with turnkey agents and custom workflows.
• The platform supports Answer Engine Optimization (AEO) to ensure brands are present in AI-generated answers.

Conductor is now offering a new enterprise suite of native Large Language Models (LLM) apps, developer infrastructure, and turnkey agents, designed to help brands build, manage, and scale their visibility across AI-driven search experiences.

What used to require multiple searches, pages, and touchpoints now increasingly happens in a single interaction on LLM platforms like ChatGPT and Claude. The shift to artificial intelligence (AI) search has created a new discipline for brands: Answer Engine Optimization (AEO), the practice of ensuring your company is present, cited, and trusted in AI-generated answers. Brands are rapidly reallocating budget and resources toward AEO to secure visibility. Those who fail to invest risk becoming invisible.

Conductor’s AgentStack allows B2B marketers to deploy agentic workflows for AEO, at enterprise scale. Through Conductor’s APIs, MCP server, and LLM apps in ChatGPT, Claude, and Copilot, enterprises and partners can power agents and applications.

Why AgentStack Is Needed

Conductor’s new suite is being offered as AI is reinventing how marketing technology is built and delivered. A new model is emerging: AI-powered agents that can be customized and deployed on demand. Instead of adapting workflows to pre-built software, teams and partners can build agentic systems and custom applications tailored to their exact needs.

“Once you connect Conductor’s MCP to your AI platform or deploy our native connectors, you can build a custom version of our application in a day,” said Seth Besmertnik, Co-Founder and CEO of Conductor, in a statement. “[This reduces] reporting time by 90% while improving output, 100x your ability to produce AI search-optimized content across emails, blog posts, and product pages. You’re only limited by your imagination. And even there, we help with use case libraries and skills guides.”

What B2B Marketing Teams Can Accomplish

Conductor has spent the last four years building the foundation for this new reality. Its unified data engine brings together the intent, content, and technical signals that determine discoverability across both AI systems and traditional search, all fully connected within a single software stack.

“Agents are only as powerful as the intelligence behind them,” said Wei Zheng, Chief Product Officer at Conductor. “Conductor brings together the signals that determine discoverability across AI systems and search engines. That intelligence is what enables agents to automate meaningful marketing work.”

B2B marketing teams now have the ability to generate automated board-ready presentations grounded in real AI visibility data, track brand sentiment across AI platforms in real time, and identify which topics competitors are winning in AI-driven answers. From there, they can optimize content to close those gaps in minutes. Technical teams can monitor whether AI crawlers can access key pages to ensure discoverability and resolve issues before performance is impacted.

Who is Using AgentStack

In addition to enterprise brands, leading agencies and technology providers, including Optimizely, Razorfish, Havas, and IBM, are already building on AgentStack for their clients.

“As AI agents become central to how enterprise marketing gets done, access to reliable, unified intelligence becomes essential,” said Alexis Zamkow, Global Offering Lead, Marketing Transformation at IBM. “Conductor’s agent infrastructure provides the data foundation needed to build systems that adapt in real time across AI-driven experiences.”

Additionally, AgentStack introduces Conductor’s first turnkey agents that combine proprietary AI search and content intelligence with a zero-configuration workflow, taking content teams from insight to published, optimized content in under three minutes, no prompt engineering or technical expertise required. Unlike other agent tools that force teams into complex interfaces, Conductors’ agents are the only turnkey solution built exclusively for AEO and content teams, delivered through a guided, point-and-click experience that makes enterprise AEO automation accessible from day one.

“We’re moving from a world where marketers optimize pages to one where systems optimize presence across AI experiences,” said Besmertnik. “Companies need an intelligence layer to power those systems. That’s the role Conductor is stepping into.”

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• Salesforce’s Agentforce Operations reduces back-office bottlenecks with AI, cutting cycle times by up to 70% and manual errors by 80%.
• The platform introduces features like Intelligent Operations and Instant Blueprints, enabling faster, more accurate workflows and seamless integrations.

Salesforce introduced Agentforce Operations, a new solution designed to transform outdated, manual back-office processes into streamlined tasks managed by artificial intelligence (AI).

Many organizations deliver fast, personalized experiences for customers and employees, only to hit delays when those modern front-end interfaces connect to legacy back-office systems. Employees frequently switch between platforms, manually transfer data, and search for updates in email. These delays slow productivity and increases operational costs— Agentforce Operations bridges this gap by extending intelligent automation deep into the core systems that run the business.

By deploying specialized artificial intelligence agents to handle process coordination, data verification, compliance checks, and approvals, the new platform reduces cycle times by up to 70 percent and decreases manual data entry errors by 80 percent, according to company officials.

How Salesforce is Rethinking AI

As companies accelerate AI adoption to become agentic anterprises, Aman Naimat, SVP and GM of Agentforce Operations, has observed that most are still burdened by an underlying layer of fragmented, manual processes across supply chain, procurement, finance, and the broader back office.

“This quietly slows operations, increases costs, and limits growth,” said Naimat. “With Agentforce Operations, we’re not just digitizing those processes but rethinking them for the AI-first world, optimizing how agents and humans work together.”

When Will Agentforce Operations Be Available

Unlike legacy workflow platforms that simply route tasks, Agentforce Operations completes complex work autonomously while maintaining a complete audit trail. The solution features Intelligent Operations, where specialized agents extract data and run computations in minutes instead of hours. Personnel can interact with the system using existing tools like email, with Slack and Microsoft Teams integrations launching in June.

Additionally, the software includes Instant Blueprints, a feature that converts unstructured documents or whiteboard diagrams into working digital workflows in minutes. Business leaders can adapt these processes without developer support by using simple plain-language email updates. An integrated proactive engine flags potential delays and suggests immediate fixes before they impact the client experience.

“Salesforce’s introduction of Agentforce Operations marks an important step forward in bringing AI-driven automation to the back office,” said Ian Kahn, Principal, Commercial & Service Excellence Platform Leader, PwC US. “Together, we’re helping clients use Agentforce to transform manual operations into intelligent workflows— from AI-powered contact centers to automated onboarding and compliance— driving faster execution, greater accuracy, and more seamless experiences.”

Agentforce Operations is generally available today. Ecosystem integration features, including the ability to automatically synchronize data and trigger actions with Salesforce Flows, will enter Beta testing in May.

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• Signal stacking reveals hidden intent.
• It’s time to redefine account coverage metrics to role-based participation and stage-fit tracking.

You just finished an incredible demo. Your primary contact loved the presentation, shared your deck internally, and your pipeline looks perfectly healthy. Then, out of nowhere, the deal stalls. The problem is not your product or your pitch. Instead, the problem is that your strategy relied on a single champion.

At the B2B Marketing Exchange (B2BMX) 2026 powered by Advertising Week, industry leaders tackled this exact scenario in a session titled Champion to Consensus: Practical Buying Group Coverage That Improves Conversion. The panel, moderated by Demand.com’s Rick Robinson that featured his colleague Terry Arnold, Gorilla Logic’s Whitney Goldstein and Delinea’s John Johansen, dismantled traditional, single-lead approaches that create massive pipeline friction.

The four experts explained how B2B decisions are increasingly made not by individuals but, rather, by committees. To help teams adapt, the panel examined three persistent myths about buying group engagement and offered practical prescriptions to fix them.

Does One Engaged Contact Equal Account Momentum?

Although many sales and marketing teams falsely believe that a highly engaged champion means the entire account is ready to buy, the reality is quite different. Two-thirds of B2B buying committees now consist of six or more stakeholders.

The prescription for mitigating this risk is proactive engagement. Teams must define required roles early in the process and run targeted plays to handle objections before they become deal-killing vetoes. Marketing and sales must work together to build narratives that resonate across the entire organization — from executive leadership down to daily tactical users.

Arnold highlighted how marketing teams can structure this approach effectively by grouping stakeholders and mapping content to these clusters. By doing so, teams can ensure no critical voice is left in the dark.

“We create role-based clusters, which basically start to look at specific levels,” he explained. “We break that out so that, in marketing, we are engaging each of those different roles in a way which is relevant to the issues that they’re trying to solve.”

Does High Intent Equal Account Readiness?

Intent data has become a staple for revenue teams, leading to the assumption that high intent automatically equals account readiness. However, intent is almost always persona-specific, the panel members observed. Just because one mid-level manager is researching a problem does not mean the broader buying group acknowledges the issue or has budget allocated to fix it.

To combat this, teams must validate intent with role breadth and stage fit. A single signal is just a starting point. More important is for marketers to look for signal stacking — evidence that multiple people within the same account are researching related topics. Furthermore, as search behaviors shift, teams must optimize their content to leverage Large Language Models (LLMs) and Answer Engine Optimization (AEO) to identify hidden intent.

Goldstein stressed the importance of questioning initial data and demanding verifiable proof of momentum, stating, “I look at intent as a clue, not necessarily the conclusion. What I’m trying to do is make our pipeline predictable. And so, we really do need to distinguish what is the signal versus what is the noise.” Signal stacking, she said, is a great strategy for doing so.

How Should Teams Measure Account Coverage?

For years, marketing success was graded on lead volume. And many teams still believe that account coverage can be measured with Marketing Qualified Leads (MQLs), clicks, or a handful of hot prospects. But here’s the reality: Coverage is actually about role participation, depth of engagement and stage fit. A high volume of leads means nothing if they all sit in the same department and ignore the financial or operational stakeholders.

The prescription is a fundamental shift in tracking. Revenue teams must track exactly who is engaged, identify which key roles are missing, and define the precise next action to bridge that gap. An operations narrative that hasn’t been communicated represents a massive structural risk to the deal.

Measuring coverage means looking at the balance of engagement across the entire account. Johansen shared a practical way that his team enforces this mindset through systemic tracking.

“The answer for me is how many people you can get attached to the opportunity in your CRM,” Johansen said. “Starting to work on that behavior and being able to say who are you engaged with [and] add them here. And it also gives us that signal to ask, ‘OK, well, where are we lacking coverage?”

How Can Revenue Teams Shift from Champion to Consensus?

The transition from champion to consensus requires a complete shift in how revenue teams operate. Arnold pointed out that building structural coverage demands tailored narratives for every layer of the business. “If teams fail to communicate value to the tactical, operational, and executive levels simultaneously, deals will inevitably stall at the finish line,” he said.

Goldstein reinforced that marketing must build a foundation of credibility and proof. Relying on anonymous website traffic or isolated clicks is no longer enough to forecast accurately.

“Teams must demand verified engagement across multiple first-party touchpoints, ensuring that content drives measurable outcomes and answers the diverse questions of the entire buying collective,” she offered.

Johansen summarized the cultural shift required between sales and marketing, saying, “Both departments must share ownership of the pipeline and stop treating committee penetration as solely a sales responsibility.”

But the most important takeaway from the session, which the entire panel echoed, serves as a warning for modern revenue teams: Don’t confuse activity with coverage. True pipeline health only exists when the entire buying group moves forward together.

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• Xactly and ServiceNow introduce the Dispute Management AI Agent to streamline compensation inquiries and workflows.
• The integration focuses on autonomous revenue orchestration, reducing friction and enhancing productivity for sales teams.

 Xactly has rolled out the first innovation from its AI-driven collaboration with ServiceNow: the Dispute Management AI Agent.

Powered by the Model Context Protocol (MCP) and integrated with ServiceNow Now Assist, the solution enables secure, real-time coordination between Xactly’s artificial intelligence (AI)-powered revenue platform and ServiceNow’s conversational AI to automate compensation inquiries and dispute workflows end-to-end .

The first application of this framework, the Dispute Management AI Agent, is designed to reduce the manual work of commission investigations for both sellers and administrators. By transforming compensation from a back-office ‘black box’ into a conversational, in-workflow experience, the framework allows the agent to proactively manage the investigation and resolution process, as opposed to just surfacing the data, according to company officials.

A Shift to Autonomous Revenue Orchestration

This shift is focused on reducing friction by minimizing unnecessary dispute submissions, and ensure that when questions do arise, they are resolved within a single, AI-guided interaction. The result is a more transparent, frictionless environment that allows both sellers and administrators to stay focused on driving revenue, said Chris Li, Chief Product Officer at Xactly.

“This solution marks a shift beyond just AI to intelligent, autonomous revenue orchestration,” said Li in a statement. “By enabling our AI to securely collaborate with ServiceNow’s Now Assist, we eliminate the friction tax for sales teams and turn complex compensation data into an instant, conversational asset that drives measurable productivity.”

What Now Assist is Designed For

This release is the first of a fleet of agents to be powered by the Xactly and ServiceNow agentic framework, with a focus on efficiency through autonomous automation to move from static integrations to intelligent automation across revenue workflows.

Now Assist is designed to bring contextual, AI-driven insights directly into the workflows where work gets done, said Anandan Jayaraman, Vice President, Product, Sales CRM at ServiceNow.

“Xactly and ServiceNow’s Dispute Management Agent demonstrates how agent-to-agent orchestration can eliminate manual processes and accelerate resolution cycles for revenue teams,” said Jayaraman. “Together, we’re helping customers unlock what’s only possible when data, AI, and workflow converge – autonomous resolution at enterprise scale.”

To learn more about Xactly’s agentic capabilities within the ServiceNow ecosystem, visit our website.

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• AI allows marketers to repurpose single live events into extensive libraries of targeted content, significantly extending the lifespan and reach of event messaging.
• By connecting event engagement data with multi-channel ABM campaigns, B2B marketers can turn trade shows into measurable drivers of pipeline creation and revenue.

Personalized and Efficient. That is the needle B2B marketers look to thread in the age of artificial intelligence (AI). AI has become a strategic initiative for those hosting both in-person and digital event as interactive event technologies are drivers to marketers who attend and participate as trade shows are a $15 billion market where 52% of business leaders say is their highest-ROI marketing channel.

This is happening as our 2026 B2B Trends Research Report found 89% of marketers report that evolving buyer behaviors and preferences are a top challenge, forcing a departure from traditional engagement models. Buyers now expect highly personalized, seamless, and digitally-native experiences. This shift requires marketers to invest in deeper data analysis and more sophisticated personalization tools to meet customers where they are. The days of one-size-fits-all campaigns are definitively over, replaced by a need for nuanced, account-specific strategies.

The value of face-to-face meetings compared with other business initiatives is remarkably strong— more than 70 percent say that events are either somewhat or significantly more valuable than other such initiatives, according to according to Northstar Meetings Group. Interactive event technologies is seen as a key to capitalizing on these meetings.

How AI Is Impacting Interactive Events

AI transforms conferences from passive learning experiences into personalized, highly efficient events for B2B marketers by utilizing predictive analytics for attendee targeting, generative AI for content creation, and AI concierges for real-time logistics.

“Events are shifting from one-time, isolated moments to integrated, always-on experiences within a broader go-to-market strategy,” said Keith Turco, Madison Logic CEO. “Marketers are under increased pressure to prove impact beyond attendance, which is driving a shift toward measurable pipeline contribution and buying group engagement.

“At the same time, there’s a growing recognition that a single attendee doesn’t represent a deal. The most successful event strategies are focused on engaging multiple stakeholders across the buying group before, during, and after the event.”

Detailing AI Use

Events a pivotal role in B2B growth strategies, with in-person and virtual gatherings, like hybrid roundtables and small-group meetings, gaining popularity. The events are being utilized to collect valuable first-party data, which is essential in today’s privacy-first marketing environment. American Express Global Business Travel’s 2026 Global Meetings and Events Forecast found AI is being used for event planning, attendee communications, during events, and for post-event evaluation. Top uses of AI include:

• Delivering AI-powered event apps (40%)
• Sponsor and attendee matchmaking (35%)
• Generating creative concepts and themes (34%)
• Content creation with tools like AI writing assistants (31%)
• Tracking attendee engagement (31%).

“AI will soon power much of what happens behind the curtain, acting as a critical assistant that helps event organizers reduce planning friction and enable more personalized face-to-face moments at scale,” said McNeel Keenan, vice president of product development at Cvent, told AMEX. “But even as technology advances, events will continue to be decidedly human. In fact, in an AI and tech-driven world, authentic connections will likely stand out even more.”

Current AI Uses at Conferences

The human touch was amplified by a Hilton survey that found 84 percent of attendees prefer in-person work events. While attendees seek authentic human connection, technology serves as a vital support system that enhances the overall experience. Today’s events deploy AI-driven tools that streamline logistics— from frictionless check-ins and personalized schedules to real-time communication via an events app.

Notably, 67 percent found AI helps personalize their experience by delivering tailored content recommendations, connecting them with like-minded professionals, and suggesting optimized networking opportunities. Two in three attendees report that AI-powered networking tools help them make meaningful connections more easily, while 65 percent express interest in AI assistants to help them prepare for meetings and navigate complex event agendas.

But beyond the content and personalization it provides, interactive event technologies impact the bottom line. Research from the Center for Exhibition Industry Research showed that interactive exhibits are 52% more likely attract attendees compared to traditional static displays. Booths incorporating gamified elements see 40% higher foot traffic with a three-minute interactive experience converts to lead capture at roughly 85%, compared to approximately 10% for a brief booth conversation.

How Does B2B Marketers Connect Event Engagement to Revenue?  

While event success previously was measured by surface-level metrics like registrations or attendance, AI enables a much deeper understanding of who engaged, how they engaged, and what that activity signals in terms of pipeline progression and deal readiness.

“With AI-powered insights, marketers can identify which accounts and buying group members are most likely to attend and convert, while also delivering more personalized engagement before and after the event,” said Turco.

Additionally, AI allows for automation to enable coordinated, behavior-driven outreach across channels without relying on manual follow-up— orchestrating a multi-channel ABM campaigns around events for example.

“Rather than relying on manual follow-up, marketers can trigger coordinated engagement across display, social, email, and content based on attendee behavior,” added Turco. “The result is a more connected view of ROI where events aren’t just a lead source, but a measurable driver of pipeline creation, acceleration, and revenue impact.”

Detailing Content Opportunities

AI integration is enhancing event experiences by automating insights from keynote speeches and repurposing them into content such as blogs and videos. At the same time, conversational AI and chatbots are revolutionizing customer engagement by addressing complex B2B queries.

The subject of his session at B2BMX 2026 and in their The 2026 Digital Engagement Benchmarks Report, On24’s Mark Bornstein VP, Marketing and Chief Evangelist detailed how marketing professionals consume content in shifting in a large way. Audiences are showing up in record numbers, but they demand personalization, interactivity, and always-on access. AI, automation, and content hubs are focused on buyers and delivering measurable ROI.

In 2025, the average webinar attracted 239 attendees, marking an 11% increase from the previous year with attendees stayed engaged for an average of 49 minutes. Total engagement per webinar jumped by 18%, generating over 400 unique interactions per session.

Repurposing Event Content

“You can capture this level of attention by integrating live polls, Q&A features, and downloadable resources directly into your event console,” said Bornstein. For example, the average webinar now sees 150 poll responses and 14 questions per session. These interactions provide valuable first-party data. as sales team can use these precise buying signals to tailor their follow-up and close deals faster.

Marketers are heavily adopting AI to repurpose their event content, having the ability to turn a single live event into a vast library of targeted assets, instantly transcribing webinars, summarizing key takeaways, and generating promotional clips.

The creation of all derivative content grew by 37% year over year— production of key moment video clips skyrocketed by 2.5X, while AI-generated blog posts and e-books increased by 2.4X, said Bornstein.

“AI and automation allow you to scale your output without sacrificing quality,” he said. “This automated workflow ensures your best ideas reach buyers across paid, earned, and owned media channels long after the live broadcast ends.”

How to Overcome the Challenges of Virtual Events

What started as a temporary workaround during the pandemic, hybrid and virtual event formats have evolved into a strategic advantage. These events give marketers the ability to scale reach, engage broader buying groups, and extend the lifespan of event content well beyond a single moment in time.

But, as Turco notes, the introduce new challenges— fragmented attention and the difficulty of sustaining meaningful engagement in digital environments. The event itself can no longer carry the full weight of engagement.

“That’s where a multi-channel ABM approach becomes essential,” he said. “Marketers can build awareness and drive registration through targeted pre-event campaigns, reinforce key messages during the event through complementary channels, and continue the conversation afterward by re-engaging both attendees and non-attendees with personalized follow-up.”

Another advantage is hybrid formats can unlock new opportunities to engage buying groups more holistically. Different stakeholders can interact in different ways with some attending in person, others virtually, and others through post-event content. “When orchestrated effectively, this expands internal alignment within target accounts and increases the likelihood of moving deals forward,” said Turco.

Why Personalization is a Priority

B2B marketers are consistently on the search to make their content more personalized. According to On24 officials, webinars featuring personalized offers saw a 118% increase in clicks and organizations using personalization generated four times as many meeting bookings per webinar.

To maximize ROI, Bornstein urged organization to implement interactive tools that capture first-party data during every live session. That data then can be fed into their MarTech to deliver hyper-relevant content hubs.

“Stop treating your webinars as isolated activities,” said Bornstein. “Start viewing them as the foundation of an intelligent, always-on campaign.”

The Data-ABM Connection That Conferences Provide

To achieve results, data needs to be treated as the foundation of modern event strategy. The most effective marketers are using data not just to report on events, but to design them by shaping everything from who gets invited to how each interaction is experienced.

“By leveraging account-level and buying group insights, marketers can prioritize the right accounts, tailor messaging to specific roles within the buying group, and personalize event experiences based on known interests and past engagement,” said Turco. “This ensures that every touchpoint feels relevant and intentional, rather than one-size-fits-all.”

Data becomes even more powerful when paired with a multi-channel ABM approach. For example, if only one stakeholder from a target account attends an event, that engagement doesn’t have to exist in isolation. Data can inform how to extend personalized follow-up to the rest of the buying group, effectively amplifying the impact of that single interaction across the account.

“Ultimately, data-driven decision-making enables marketers to move beyond generic event experiences and toward highly relevant, account-centric engagement strategies that drive stronger pipeline outcomes,” said Madison Logic’s CEO.

What is Working on Conference Floors

Walk on any trade show floor and you will see booths incorporating virtual reality games, motion simulators, and branded interactive installations that can be deployed at scale. Interactive booth games are the primary mechanism through which exhibitors capture prospect data. The average cost per lead at a trade show is $112, compared to $259 for a traditional field sales call.

This matters because 81% of trade show attendees arrive with buying authority. Two-thirds are entirely new prospects that exhibitors have not previously reached. When trade show booth games convert those attendees into registered leads at rates approaching 95% for the most engaging formats like racing simulators, the channel starts to look less like marketing and more like a sales pipeline with better conversion rates than most digital campaigns.

The results have encouraged a wider market to follow— 61% of exhibitors now prioritize personalization in their booth experiences, and 57% use digital business cards or QR codes to streamline contact exchange-both indicators that the trade show floor has moved decisively toward technology-driven engagement.

Driving Stronger Pipeline Outcomes

Turco stressed that first-party event data is one of the most valuable assets marketers have, but its true impact depends on how effectively it’s activated after the event. The most successful marketers treat event data not as a static output, but as a catalyst for ongoing engagement. Importantly, even limited engagement can be expanded into broader influence across the buying group.

“By mapping attendee behavior back to accounts and buying groups, marketers gain a more complete view of deal context and can tailor follow-up based on engagement levels, interests, and stage in the buyer journey,” said Turco. “This allows for more relevant, personalized outreach that continues the conversation rather than restarting it.”

Using those signals to guide outreach to additional decision-makers helps amplify the event’s impact within the account. Over time, these insights inform future strategies—. understanding which accounts engaged, what content resonated, and how buying groups interacted enables marketers to continuously refine their approach. Interactive event technologies tuns events into an ongoing source of intelligence that drives stronger pipeline outcomes.

The post Why AI is the Ultimate Tool for B2B Event Marketers appeared first on Demand Gen Report.

• Pinterest’s high-intent audiences can now be targeted on Connected TV through tvScientific’s platform.
• Early testing shows a 73% increase in unique household reach and a 24% lift in new customer acquisition.

tvScientific by Pinterest announced on April 27 that advertisers can now reach Pinterest’s exclusive high-intent audiences off of Pinterest and on the biggest screen in the house, TV.

This launch, the first step in a broader vision for a unified cross-screen advertising experience, marks the first major milestone since Pinterest completed its acquisition of tvScientific in February 2026, bringing together Pinterest’s first-party audiences and tvScientific’s performance advertising platform.

As streaming platforms have become a primary way consumers watch TV, movies, and other content, advertisers are increasingly seeking more channels to reach high-intent audiences and drive measurable performance. Connected TV (CTV), internet-connected devices like smart TVs, streaming sticks, and gaming consoles that deliver streaming content directly to the big screen, delivers the reach of traditional TV with the precision of digital advertising.

How Large is the CTV Market

Last year, CTV ad spend reached $32.45 billion in the United States and is expected to surpass linear TV ad spending, to more than $45 billion by 2028.

“Pinterest brings a distinct opportunity, with more than 600 million monthly active users and growing,” said Lee Brown, Chief Business Officer of Pinterest in a statement. “Because of how users search and shop on the platform, we can give advertisers new ways to reach people at every stage of the shopping journey, from discovery to buying, both on and off Pinterest.”

Why this is an Opportunity for Marketers

tvScientific by Pinterest is the first ad platform to offer direct access to the social media platform’s high-intent audiences for CTV campaigns. Advertisers can use Pinterest’s commercial intent signals to reach audiences across premium inventory on the biggest screen in the house, while leveraging tvScientific’s artificial intelligence (AI)-powered optimization technology.

As a result, brands can reach their target audience at scale and drive measurable performance. On average, when tvScientific AI is enriched with Pinterest’s high-intent signals, it leads to a +27% increase in outcomes driven per $100 in spend, with purchases up +65%.

“The real opportunity for advertisers is turning consumer intent into action, and Pinterest’s signals are unique because they reflect what people are planning, not just what they’ve already done,” said Jason Fairchild, CEO of tvScientific by Pinterest.

LG Success on CTV

Early testing from advertisers demonstrates tvScientific by Pinterest’s scale and performance— LG expanded its existing audience approach and delivered a 73% increase in unique households reached with access to Pinterest audiences. This additional reach drove a 24% lift in net new customer.

According to Fairchild, this shows that Pinterest intent can help advertisers find more of the right viewers on CTV and turn incremental reach into measurable business results, according to company officials.

“Every month, there are more than 80 billion monthly searches on Pinterest, and by bringing those signals into tvScientific, advertisers can run more precise CTV campaigns and optimize toward the business outcomes that matter most,” said Fairchild.

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• StackAdapt’s MCP Server integrates campaign intelligence into AI tools, enabling real-time performance insights and optimization.
• The server supports conversational access to campaign data, replacing manual reporting and fragmented workflows.

StackAdapt on April 21 announced the general availability of its Model Context Protocol (MCP) Server, a new integration that makes campaign intelligence directly accessible within artificial intelligence (AI) tools such as Claude.

The MCP Server extends the capabilities of Ivy, StackAdapt’s AI marketing assistant, beyond the platform, allowing advertisers to monitor performance, audit creative, and analyze campaign data in real time without needing to log into the platform directly.

By connecting StackAdapt to the AI tools teams already use, including large language models, agents, and workflow automation systems, the integration enables conversational access to campaign intelligence— replacing manual reporting, spreadsheets, and fragmented workflows with a single prompt.

Explaining StackAdapt Integration

Designed for both business leaders and technical practitioners, the MCP Server gives decision-makers across B2B marketing and strategy direct visibility into campaign performance while enabling teams to integrate that data into internal systems, dashboards, and custom AI workflows.

“AI is reshaping how teams work, yet most platforms still require users to operate within their own environments,” said Yang Han, Co-founder and CTO at StackAdapt, in a statement. “The MCP Server brings StackAdapt’s intelligence into the AI workflows where decisions are already being made, giving customers direct, real-time access to their campaign data without added complexity.”

How Does MCP Server Help Marketers

The new server is designed to be completed in minutes with no engineering resources, API integrations, or additional cost required. Once connected, users can ask natural language questions about their campaigns and retrieve performance insights, including pacing, audience-level results, and creative status.

At launch, the MCP Server provides access to campaign configuration, performance metrics, and creative assets across all supported channels, including connected TV (CTV), display, native, audio, digital out-of-home (DOOH), and programmatic linear TV.

Beyond conversational access, the MCP Server lays the foundation for more advanced, agent-assisted workflows, according to company officials. AI systems can continuously monitor campaign performance, surface insights, and facilitate automated triggers based on user defined guardrails across tools and teams. By making programmatic intelligence accessible in real time, StackAdapt enables advertisers to augment manual analysis with always-on optimization powered by AI.

While many platforms are embedding AI within their own environments, StackAdapt is making its intelligence accessible across the broader AI ecosystem, said Han. Built for the open web, the MCP Server spans all channels and supply sources without tying advertisers to a single platform or inventory ecosystem, bringing domain-specific programmatic intelligence directly into AI workflows, rather than relying on generalized outputs.

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• Adobe introduces CX Enterprise, an AI-powered system to streamline customer lifecycle management.
• CX Enterprise integrates with leading AI platforms to deliver personalized, scalable customer experiences.

At the Adobe Summit last week, unveiled Adobe CX Enterprise, a new end-to-end agentic artificial intelligence (AI) system offered to simplify how businesses manage their entire customer lifecycle, from acquiring and engaging prospects to driving conversion and lasting loyalty.

Customer Experience Orchestration (CXO) is changing in the era of agentic AI as agents become critical resources that can help accelerate complex workflows, from on-brand content production to one-to-one personalization. With the introduction of CX Enterprise, Adobe is solving CXO with a new class of intelligent systems.

Grounded in decades of domain expertise in data, content and customer journeys, the CX Enterprise is an anchor for AI agents that are reliable, auditable and can understand context. CX Enterprise powers agents that can help scale impactful, personalized customer experiences so that interactions consistently reflect brand guidelines.

How Adobe is Enabling the Scaling of AI Agents

Anil Chakravarthy, President, Customer Experience Orchestration Business, Adobe, commented that CX Enterprise is powered by the new Adobe Brand Intelligence, a continuously learning reasoning engine that can capture evolving brand signals, and Adobe Engagement Intelligence, a decisioning engine optimized for customer lifetime value, to deliver personalization at scale.

“Adobe CX Enterprise enables businesses to scale agentic AI with a fully customizable solution that is tailored to the needs of their organization, moving teams beyond AI experiments to tangible business outcomes,” said Chakravarthy in a statement. “This end-to-end solution fits naturally into any environment, built to work alongside tools across leading AI platforms with seamless interoperability.”

A List of Adobe’s AI Partners

CX Enterprise is being offered with multiple access points and forward-deployed engineers that can tailor solutions to real workflows. A composable architecture that works with various technology stacks provides businesses flexibility and control, including extending agentic skills and workflows across Adobe and partner solutions from Amazon Web Services, Anthropic, Google Cloud, IBM, Microsoft, NVIDIA and OpenAI.

The new agents streamline time-intensive tasks and help businesses to meet customer retention and growth objectives. Powered by Adobe Experience Platform Agent Orchestrator— which enables teams to build, manage and coordinate agents across Adobe and third-party ecosystems— the agents are natively integrated into new and existing Adobe solutions across areas such as customer engagement, content supply chain and brand visibility.

By managing the quality of output and governance, the Adobe is extending these capabilities by bringing the agents into surfaces including Amazon Quick, Anthropic Claude Enterprise, ChatGPT Enterprise, Gemini Enterprise, IBM watsonx Orchestrate and Microsoft 365 Copilot.

A Look At CX Enterprise’s Key Benefits

Other offerings in CX Enterprise will include:

• Agent skills catalog: This set of agent skills make it easy for businesses to create custom workflows by packaging reusable instructions, such as reviewing performance metrics to drive content creation or journey orchestration workflows.
• Developer tools: CX Enterprise will provide access to Adobe’s agentic skills, MCP servers and the infrastructure needed to build customizable use cases. It will enable developers to incorporate  agentic capabilities directly into tools from Anthropic, Google Cloud, Microsoft, and OpenAI among others, with a composable platform that makes it straightforward to bring functionality directly into the tools used daily by marketing and creative teams.
• Adobe CX Enterprise Coworker: Businesses have the flexibility and control needed to bring AI agents into daily workflows with confidence, increasing levels of automation that will help teams drive business outcomes, while maintaining human oversight and control. The goal is to improve the capability, choice and automation that transforms how brands engage customers.

Anjul Bhambhri, SVP of engineering, Customer Experience Orchestration, Adobe, further detailed that the CX Enterprise Coworker is designed to execute tasks based on defined business goals, coordinating work across multiple agents by translating clear objectives into multi-step actions, said

“Coworker will be the next step for businesses that are retooling marketing workflows to help teams take advantage of agentic AI technology,” said Bhambhri. “By synthesizing intelligence from across Adobe applications, enterprise systems, and leading AI platforms, we are closing the gap between insight and action, enabling brands to deliver one-to-one personalized experience at scale.

“This is what it means to put the full power of agentic intelligence to work for marketing teams.”

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