The management issue is not whether AI is visible in go-to-market; it is who owns the system of record for claims, proof and approvals. When buyers use AI to screen vendors and employees use AI to produce content, the organisation needs one accountable chain for message integrity, evidence standards and escalation. Otherwise, faster production simply multiplies inconsistent positioning and ungoverned promises.
That shifts the operating model question from content volume to control points. Teams should define where humans must approve claims, what qualifies as acceptable evidence, and how legal, product marketing, sales and customer success resolve conflicts. The practical trade-off is speed versus assurance: too much control slows response time, but too little control creates regulatory, reputational and pipeline risk. Next question: which artefacts need formal review before they can be reused in-market?
There is also a portfolio choice hiding inside the AI conversation. Not every automation effort should be treated as a productivity project. Some use cases reduce cost, while others reduce commercial risk by improving consistency across the funnel or by making technical claims easier to defend. Leaders should ask which outcomes matter most this quarter: shorter cycle time, higher conversion, lower compliance exposure, or better post-sale retention. If the answer is mixed, the funding model should be too.
Finally, the buyer journey is becoming a change-management problem for the vendor, not just a channel problem. If AI systems are shaping discovery and evaluation, then enablement, analyst relations, customer proof and internal messaging all need to reinforce the same story. The next leadership questions are straightforward: who owns that story, how is it measured, and what evidence would make the organisation stop or redesign the programme if trust starts to slip?
Over three packed days at Money20/20 in Amsterdam, the halls were buzzing about two things: trust and agentic commerce.
Behind the buzzwords, trust is really three concrete demands from banks: whether they can rely on AI they didnโt build; whether customersโ money, identity, and data stay safe with the bank (including how the bank itself uses them); and whether a nondeterministic decision can be proven to a regulator under DORA and the EU AI Act. Agentic commerce lives in a narrower reality than the word implies: Agents today work at discovery and assisted checkout stages, not autonomous buying. The consumer demand and control layer that grounds an agent in policy and identity isnโt there yet.
For tech vendors, this means naming the specific problem you solve and not hiding behind a category label. The clearest way to do that depends on what you sell:
- Fraud solutions. If you sell fraud solutions, acknowledge that AI agents now play on both sides. Attackers use them to industrialize deepfakes and synthetic identities; fraud teams are starting to deploy their own detection agents; and an agent acting for a customer now has to be verified itself before it moves money. Broadcast that you are keeping pace in an arms race: a stack that adapts, corroborates across layers, can verify agents (not just people), and ideally demonstrates ROI from comparable deployments.
- Payments solutions. If you sell payments solutions, the European dynamic is important to point out. Account-to-account payment is growing through open banking, and domestic schemes are interconnecting to stand independent from global card networks. The more sovereign schemes there are, the more interoperability becomes essential.
- Banking platforms. If you sell banking platforms, your buyerโs job is to keep the lights on and innovate within budget and legacy constraints. DORA makes system resilience a legal baseline, and the EU AI Act demands that an AI-driven decision must be explained and audited. Lead with de-risking the strategic change.
And for your own go-to-market (GTM) operations, the bigger shift is this: AI is changing how the function runs. Bear in mind:
- You have a new audience, the LLM. Forresterโs Buyersโ Journey Survey, 2025,ย shows that 91% of business buyers used or plan to use a generative AI (genAI) tool to support their purchase process. The genAI tool is the audience and influencer, sitting alongside your human buyer. What gets your brand surfaced is specific, authoritative coverage of the problem you solve. To get ahead, youโll need to build credibility off your own site, such as third-party communities, reviews, analyst coverage, and PR, because models often prefer to cite external sources. Anticipate the whole arc of the inquiry: Buyers on these platforms ask follow-up questions instead of clicking through, so your content has to answer not just the first question but the chain behind it. Use Best Practices For Answer Engine Optimization (AEO) as a guide for your large language model (LLM) content development.
- You should use AI inside your own team. Pioneering marketers are already doing this, and the first effect is the obvious one: Producing content and surfacing the right material for sales gets faster and cheaper. The content bottleneck that teams have complained about for years is easing. Align AI Agent Use Cases With Strategic Marketing Initiatives To Accelerate The Revenue Engine can help you deploy your B2B marketing AI more effectively.
- AI doesnโt touch the hard part. The persistent challenge in selling into banks isnโt producing content โ itโs holding one consistent message across the whole sales cycle and continuing to deliver on it after the deal closes. A faster content engine doesnโt create that consistency. If marketing and sales are working from different stories or different goals, AI just produces the inconsistency faster. Fixing it still takes aligned metrics and a close working relationship between the two teams โ the same operational work it has always taken. Use Master B2B Growth With The Power Of Aligned Revenue Planning to guide your marketing-sales alignment planning.
Want To Get This Right?
This is the work we do at Forrester Consulting. Our offerings help vendors position themselves against buyer needs and competitors to build messaging that holds up across the cycle and resonates with the people making the decisions. If this is your world, letโs talk.
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