2026: In Pursuit of AI Methodology

As organizations hone their focus on agentic AI, they’re learning that a few strategic agents will outperform many scattered ones. We think that a handful of these “hero agents,” trained and optimized for the proper use cases and carefully integrated with corporate datasets, apps, and systems, will yield far more value to any given team or function than many lightly used agents.

Many people predict that the biggest shift from AI in go-to-market during 2026 will be in sales enablement, and I agree. The category is moving beyond simply delivering the right content at the right time toward fully agentic platforms that support sales teams before, during, and after customer interactions, while continuously personalizing training at the individual rep level. This represents a true reinvention of sales workflows—and it’s already taking shape.

Pipeline stops being the marketing scoreboard. The new unit of performance is revenue across the full customer lifecycle, because AI removes the human constraints that forced siloed handoffs. The breakthrough is not replacing humans, but surpassing human limitations in recall, real-time response, and personalization, so the buyer never has to start over. Leaders who treat AI as change management and redesign the experience from scratch will capture demand more efficiently and build trust at scale.

Over the next two years, AI won’t just automate go-to-market motions. It will collapse the distance between strategy and execution altogether. The traditional operating rhythm of decide → plan → deploy → measure → adjust will be replaced by something far more fluid: an adaptive GTM stack that rewrites itself in real time, collapsing the time between strategy and execution altogether.

Meeting note-takers and transcripts tools became systems of action. Today, most people use meeting note takers to simply act as transcription tools and then help them remember action items. Meetings are so much more valuable. Most meetings contain rich, vibrant information that sellers can use in a whole host of ways to create action in a business. Everything from coaching bots to case study generators to blog post writers to prototype creators. Any information that is discussed in a meeting can be valuable context for a prompt to generate something valuable for your business.

In 2026, marketing teams won’t say they’re ‘using AI’, but rather that they’re building intelligent systems that help them not just do more, but do better. The shift from manual workflows to agentic marketing means AI handles the operational lift, while humans double down on strategy, creativity, and brand differentiation. The teams that win will be the ones that treat agents as collaborators and teammates, not as tools or shortcuts.

AI will standardize account plans and points of view, so differentiation moves back to relationships and stakeholder navigation. The winning seller will use automation to arrive prepared, then win in the room by building trust and executive alignment. Frontline managers will regain time by automating the reporting machine, so they can focus on closing deals and staying close to the product market truth.

Customer expectations will rise toward hyper-personalized, conversational experiences, and brands will be judged on whether they can deliver them with trust. Adoption is not a technology rollout. It is change management: agents must fit existing workflows first, earn trust through low-risk “pre-work” assistance, and only then graduate into autonomy. The strongest systems will separate authenticated from unauthenticated personalization, protect privacy, and invest in provenance, content credentials, and machine-readable brand identity as both humans and agents become the audience.

In 2026, the most disruptive force in GTM will be customer-controlled AI agents. Discovery, evaluation, and even purchasing will increasingly happen inside AI interfaces that buyers trust, not on vendor-owned channels. Attribution will degrade further, while brand, narrative, and content structured for answer engines become the primary levers of influence.

Buyers simply have a lower tolerance for buying experiences that don’t reflect the speed of their research and consideration process. Everyone talks about agents, but what you’re really looking at is repeatable, high-quality experiences that don’t sacrifice the quality of the interaction, and AI makes that possible.

Buyer behavior is shifting to people asking AI for answers, and the data proves it. Within a five-month span, we saw AI chatbots acting as the starting point for research jump from 29% to 50%, and shortlists are collapsing toward one choice as trust in AI rises. Winning in 2026 means engineering your AEO strategy to show up in the answers. Map the questions, influence the citation sources, and drive consensus by keeping positioning consistent across every citation where models crawl.

Agentic AI will become mandatory across sales, marketing, and service. But onboarding AI agents is unlike anything we've ever done before. Teams that treat agents like workers, rather than a software install, will move faster and gain a competitive advantage. The stack conversation shifts from which tools to which agents can help us run the business dramatically quicker.

In an AI-flooded world, connection is a differentiator. Marketing leaders must continue to invest in community, PR, and in-person moments that build trust while using AI behind the scenes to create as many opportunities to connect as possible. The future of customer experience blends AI-powered scale with deliberate human effort. This is where the alpha in marketing remains.

The number of SDRs will decline as AI handles real-time account research based upon public and proprietary data and mapped to the ICP. This will shift messaging to sales reps for high-quality, value-add messaging targeting specific personas and relevant use cases. At the same time, customers will deploy AI gatekeepers to block non-specific outreach and prioritize incoming messaging based upon company, persona, and use case specifics.

In 2026, reasoning AI will begin replacing rules-based logic, starting with lead scoring, data management, and journey orchestration. Instead of static nurture tracks, AI will dynamically sequence actions based on real-time signals: which offer, which channel, which content, and what timing. Think of it as AI acting as a DJ, creating personalized playlists for every buyer and account.

AI transformation stalls when it’s framed as an individual obligation instead of an organizational operating model. The next step is team-based collaboration: shared workflows, shared definitions, and shared knowledge, not scattered prompting. Companies will see early warning signs when “AI told me” produces conflicting answers in reviews and when power users outpace everyone else. Leaders who model experimentation, build time for testing, and enforce transparency about what AI produced will turn AI into a team sport and reconnect trust, taste, and outcomes.

Integration is the gating factor for agentic success. AI impact will move from individual productivity to P&L only when enterprises isolate real business processes, codify domain memory, and add guardrails that make probabilistic systems repeatable. The shift is from deploying models to operationalizing context: unlocking tacit knowledge across functions, embedding memory layers, and designing new workflows that were previously impossible. Organizations that treat AI as foundational infrastructure, not an employee app, will finally exit pilot purgatory.

In 2026, the most significant AI paradox has arrived: the more perfect LLM-generated content becomes, the more the market craves human authenticity. For years, GTM was about brands talking at buyers; today, GTM is about people talking to people. As AI SEO engines pivot to favor content from actual people from Reddit threads, YouTube creators, and raw review sites over corporate blogs, the corporate voice is falling flat. To find "Alpha" in 2026, we have to go outside the safe brand pocket.

Agentic monetization shifts value capture from seats to outcomes, as software performs real work, pricing and packaging tied to licenses collapse. The largest deals move from software budgets to labor and BPO spend. Companies that give their best reps controlled freedom to price against delivered value while managing margin in real time will unlock materially higher ACVs and more durable gross margins.