Smarter Buyers: How AI Is Rewriting the B2B Playbook for 2026

As the CEO of a SaaS company, I’ve been buying technology for over a decade. And I can say with confidence: procuring new tech today feels nothing like it did even one year ago, let alone ten.

The process of bringing new technology to market used to be linear. A company would identify a customer problem, design a solution, launch, and sell through human-led channels. Now, as I head into our planning cycle for 2026, one thing has become abundantly clear to me: that linear motion no longer exists.

Why? Because AI has become the engine driving how technology is discovered, evaluated, and trusted. This shift is already transforming how the tech industry competes. The pace of AI-driven innovation has not only reshaped how we build technology, it has also redefined how the entire market decides what deserves attention. Technology companies must take note.

AI informs tech choices before the first meeting

A couple of decades ago, my team and I would have met with various vendors – often in person – as one of the first steps on the path to selecting a new technology for our business. With AI, buyers today might be halfway down the decision path before they talk to a human.

Of course, technology buyers have been conducting online research for several years, if not decades. Recent Responsive research found that nine out of ten buyers come to the table prepared, conducting research before first vendor contact. In 2020, Gartner predicted that 80% of B2B sales interactions between suppliers and buyers would occur in digital channels by 2026. From my own observation, they weren’t far off the mark.

But AI is adding fuel to this shift. G2’s 2025 Buyer Behavior Report found that 79% of software buyers globally say AI search has changed how they conduct research, with 29% noting they now start research via large language models (LLMs) more often than Google. According to Responsive’s recent research, the gap is even wider: two-thirds of business buyers reported using generative AI as much as, or more than, traditional search engines for critical decisions.

For tech companies, this means algorithms are telling potential buyers your story long before a sales conversation even begins. Your digital footprint, from product pages to comments in user communities, and even your brand’s AI discoverability have become competitive differentiators.

Vendors must understand the AI-influenced buyer

In light of this shift, technology providers must understand and adapt to the modern buyer. Here are three changes to keep in mind.

1. Leadership alignment has shifted around technology.

While buying used to sit with procurement, today every business leader from product to finance to compliance may play a role. That’s because the risks associated with how we adopt or integrate AI can be just as consequential as the innovations themselves, and data quality, regulatory exposure, and model governance now shape the conversation as much as cost or performance. AI strategy has become business strategy; in fact, organizations that align leadership around AI priorities are nearly twice as likely to report above-average growth, according to McKinsey.

The most forward-thinking tech companies I know don’t treat AI as a product feature, they treat it as an enterprise capability. They’re building shared literacy around governance, model safety, and data integrity across functions, not just inside engineering; it’s become a prerequisite for responsible innovation. As we plan for 2026, I’m treating alignment around AI as a shared organizational discipline, ensuring every team understands both the potential and the responsibility.

2. AI has redefined risk and credibility.

You can’t throw a rock in Silicon Valley without hitting a new AI tool. Every company now has an “AI-powered” slide in their pitch deck. But the question buyers increasingly want answered isn’t whether you’re using AI, it’s whether you’re using it responsibly.

It’s no secret that AI is attracting increased scrutiny and oversight. In 2024 alone, the number of companies disclosing board-level AI oversight grew by more than 84% year-over-year, and more than 150% since 2022.

Today’s buyers are no less scrutinous. According to recent data, nearly half of technology decision-makers are already applying AI to critical workstreams, from market research to product roadmaps. Another 71% expect to increase AI use over the next year, and one in three say a company’s use of GenAI makes them more likely to trust that brand.

That tells me AI is no longer a real differentiator; it’s a filter for a company’s credibility. When evaluating AI claims, I now ask technology providers: How do you safeguard the data that powers your models? What’s your governance and disclosure framework? Do you test for drift or bias, and share those findings? Responsible innovation has become a new competitive edge.

3. Proof still beats promise.

One thing hasn’t changed in twenty years: my mantra in technology leadership is still “show, don’t tell.” AI can accelerate my discovery and automate communication, but at the end of the day, I need to see proof.

I’m not alone. The vast majority of buyers still say formal RFP responses are “very” or “extremely important” in their final decision. Whether it’s the accuracy of an LLM output, the transparency of training data, or the clarity of customer outcomes, tech buyers today still want evidence that technology delivers—not just in theory, but in practice, and better than the competition.

In one recent example I witnessed, a global enterprise compared two GenAI tools by asking a simple, high-stakes question: “How many employees does our company have?” The popular model pulled an outdated figure from the open internet; the other surfaced the exact, verified number from the company’s internal system. That single moment of accuracy turned the conversation from hype to trust—and trust won.

Technology leadership requires mastering the AI lens

I find myself today spending more time than ever thinking about how technology companies, including my own, are being perceived through the lens of AI. As a CEO, it’s my role to shape the process that determines how our company is evaluated, trusted, and chosen in an AI-dominated market.

We’ve entered an era where trust, proof, and governance around AI matter as much as speed and innovation. This is a crucial shift for technology leaders: a moment to turn AI-driven change into long-term competitive advantage. Tech leaders have a choice: let AI reshape your market for you, or proactively shape how your company shows up in an AI-driven buying journey. Start by elevating governance, proving your outcomes, and aligning your leadership around responsible innovation.