What Happened When AI Changed How Buyers Buy?
The old go-to-market playbook isn’t disappearing overnight, but it is being challenged in ways that were hard to imagine just a few years ago.
That was the central theme of MTLC’s September 18 Hot Topic session, Building the AI-Powered GTM Engine, where industry leaders gathered to discuss how AI is reshaping customer acquisition, revenue growth, and the future of marketing and sales. Throughout the morning, presenters and panelists explored a reality many organizations are beginning to confront: buyers are no longer discovering, evaluating, and engaging with companies in the same ways they once did.
As AI becomes embedded throughout the buying journey, growth leaders face a new challenge. Success is no longer about generating more activity. It’s about building systems that create stronger signals, more relevant experiences, and deeper trust.
We Are Entering the Era of Machine-Mediated Discovery
One of the most thought-provoking conversations of the morning centered on how dramatically buyer behavior is changing.
For years, marketers optimized for search engines. Today, more buyers are turning to AI-powered tools to research solutions, compare vendors, and gather information long before speaking with a sales representative. As a result, some of the earliest interactions with a brand are now happening through AI systems rather than traditional channels.
Panelists pointed to growing evidence that traffic originating from large language models behaves differently than traditional search traffic. Rather than browsing broadly, these users often arrive with clearer intent, making them more likely to engage and convert. The implication is significant: companies must now think not only about how they appear in search results, but how they are interpreted, summarized, and recommended by AI.
The first audience for your content may no longer be a prospective customer.
It may be a model.
The Real Competitive Advantage Isn’t More AI. It’s More Trust.
If AI is making it easier for everyone to create content, launch campaigns, and automate outreach, what becomes the differentiator?
Throughout the session, speakers repeatedly returned to the same answer: trust.
As inboxes fill with AI-generated messages and prospecting becomes increasingly automated, buyers are becoming more selective about who gets their attention. Simply increasing outbound volume is no longer enough. In fact, many traditional tactics are becoming less effective precisely because they are now so easy to replicate.
Mike Grandinetti challenged attendees to rethink the assumption that more activity automatically produces more pipeline. Meanwhile, David Chang demonstrated practical workflows focused on identifying relationships, shared connections, and contextual signals before outreach begins.
Their message was clear: AI can help identify opportunities, but relationships are still what open doors. In an environment saturated with automated outreach, warm introductions, trusted referrals, and genuine credibility are becoming even more valuable.
The Funnel Is Giving Way to the Revenue Engine
Another major theme throughout the morning was the evolution from traditional demand generation to revenue orchestration.
Historically, marketing, sales, customer success, and operations have operated as separate functions with separate goals. Today’s highest-performing organizations are increasingly treating those departments as components of a single interconnected revenue engine.
The discussion highlighted the importance of creating systems where customer insights, engagement data, and buying signals flow seamlessly across teams. Rather than optimizing for handoffs, organizations are optimizing for continuity.
This shift requires leaders to think beyond lead generation. Winning companies are focused on customer lifetime value, expansion opportunities, retention, advocacy, and long-term revenue durability. AI plays an important role in making those connections visible, but the larger transformation is organizational.
The future belongs to teams that operate around shared outcomes, not departmental metrics.
Governance and Speed Are Pulling Leaders in Opposite Directions
The practitioner panel also explored one of the most difficult challenges facing organizations today: how to move quickly with AI while maintaining appropriate governance.
Most companies recognize they need guardrails. However, panelists noted that overly restrictive policies can have unintended consequences. When approved tools can’t keep pace with business needs, employees often seek solutions elsewhere, creating security and compliance concerns of their own.
At the same time, organizations are beginning to recognize that AI-generated workflows, prompts, and proprietary data may become valuable intellectual property. That has prompted new conversations around ownership, access, and risk management.
The discussion reinforced that AI adoption is no longer simply a technology initiative. It’s a leadership challenge requiring organizations to balance experimentation with responsibility and innovation with trust.
The Skills That Matter Most Are Becoming More Human
While the technology itself dominated much of the discussion, many attendees left thinking about people.
As AI automates routine work, the skills rising in importance are not necessarily technical. Leaders pointed to judgment, curiosity, critical thinking, creativity, communication, and adaptability as capabilities that will become increasingly valuable over time.
The consensus was not that AI will eliminate the need for talent. Rather, it will change where human talent creates the greatest value.
Organizations that invest in helping employees learn, unlearn, and adapt will be far better positioned than those focused solely on tools.
The Future GTM Engine Is Built on Signals, Systems, and Human Judgment
By the end of the morning, a common thread had emerged from every presentation and panel discussion.
The organizations poised to succeed in the AI era will not necessarily be those deploying the most tools. They will be the ones that most effectively combine AI-powered intelligence with human judgment, strong customer relationships, and cross-functional alignment.
Technology is making it easier than ever to generate activity.
The real challenge is generating relevance.
And that’s where the next generation of go-to-market leaders will distinguish themselves.
Thank You to Our Speakers, Sponsors, and Host
MTLC extends its sincere thanks to keynote presenters Mike Grandinetti, Executive Fellow at Harvard Business School, and David Chang, Co-Founder of Via AI, for setting the stage with compelling insights into the future of AI-powered growth.
We also thank our practitioner panelists, Megan Anderson, Chief Customer Officer at Constant Contact; Jennifer Griffin Smith, Chief Marketing Officer at Acquia; Bill Bentley, Chief Revenue Officer at Eminence Grey; and moderator Peter Atanasoff, Managing Director and VP at Scratch Marketing + Media, for sharing practical perspectives on how organizations are navigating AI adoption, customer engagement, and revenue growth today.
Special thanks to our sponsors Draidel, Jalasoft, MIT Professional Education, and Scratch Marketing + Media, and to Synergy for hosting the event.
As the conversation demonstrated, AI may be transforming the mechanics of go-to-market strategy, but lasting growth will continue to be built on trust, relationships, and the ability to create value for customers.
JOIN US NEXT TIME: DESIGNING YOUR AI-NATIVE WORKFORCE, OCT. 21 @ WAYFAIR
