When Implementing AI, Don’t Repeat the Mistakes of the Past

Why GTM leaders must rethink how they adopt AI, not just which tools they choose

Marc Benioff recently sounded the alarm on artificial intelligence (AI) innovation outpacing customer adoption. But the real issue isn’t speed. It’s anxiety.

Every vendor now claims to be “AI-powered,” whether or not the label is deserved. Business leaders are flooded with options and paralyzed by noise. And while 98% of go-to-market (GTM) leaders say they’re adopting AI, only 10% are fully executing on those strategies.

That gap is troubling but familiar. I’ve seen this movie before back when the first generation of cloud GTM frameworks arrived.

The biggest mistake we made with legacy GTM frameworks was letting technology dictate the process. We served the tools, not the customer. If we repeat that in the AI era, we’ll again miss the chance to use AI’s full potential to drive productivity, predictability, and efficiency across every B2B sales organization.

AI implementation can’t be treated as a tech upgrade. It’s an opportunity to reimagine how we work, bringing selling back to what it started as: a human-to-human exchange of value. Here are three non-negotiables I advise my teams and peers to keep in mind when bringing AI into GTM operations.

Identify Subtractors, Not Add-Ons

The first principle of AI adoption should be consolidation.

After two decades of digital transformation, the average revenue team now manages between 12 to 25 tools. Sales reps spend more time navigating tech and executing manual tasks than selling. Yet, most companies continue layering new AI tools on top of that mess. That’s the wrong instinct.

Before you deploy any AI solution, ask: Which existing tools will this allow me to eliminate — or prevent me from buying later?

AI’s true power lies in unifying data, automating repetitive work, and collapsing workflows. If one system can replace even a few tools your team currently juggles reducing context switching, duplicate data entry, and manual steps then that’s subtraction by intelligence.

We don’t need more software. We need smarter systems that absorb complexity instead of compounding it.

Focus on Productivity, Not Just Insights

Many AI tools emphasize predictive capabilities forecasting, lead scoring, or pipeline analysis. Insight is valuable, but the metric that truly defines ROI is productivity. Every minute a rep spends documenting account plans, researching contacts, preparing for meetings, updating fields, chasing unqualified leads, or syncing systems is time not spent selling.

AI shouldn’t just predict outcomes. It should restore time and elevate execution of humans.

Predictive analytics that tell you what might happen are table stakes. Intelligent systems that automatically act on it— building territories by ICP, surfacing contacts by persona and propensity to engage, automating enrichment, personalized outreach, scheduling follow-ups, updating deals, auto-correcting forecasts, and triggering intelligent workflows— that’s transformation.

When evaluating AI for your GTM team, ask:

• How much time does this save per rep each week?
• What manual process does it eliminate entirely?
• Does it elevate execution, velocity, conversion and overall productivity?

True productivity isn’t about doing more, it’s about improving how humans perform and giving them the time to do more of it.

Redefine “AI Success” Around Human Enablement

The best AI doesn’t replace people, it amplifies them. If your AI strategy focuses on automation or headcount reduction, you’re missing the point. The real opportunity is in human optimization.

AI should make selling more personal and rewarding for both buyer and seller. It should surface insights in real time, automate the busywork, personalize communication, and help sellers stay present in every conversation. When implemented correctly, AI scales personalization.

Every implementation decision should pass a simple test: Does this technology strengthen human connection or replace it?

The companies that get this right will win the AI era not because they have more tools, but because they’ve built systems that empower people to do their best work.

The Future Favors the Bold

AI is the most powerful platform shift in human history and realizing its potential requires more than incremental innovation. It’s not a bolt-on or a chat interface, it’s a once-in-a-generation opportunity to rebuild software and workflows from first principles.

Every company today faces a choice: adopt AI as a widget feature or rethink how they work because of it. The latter takes more courage, but it’s the only path to lasting transformation and competitive differentiation.

During the Industrial Revolution, factories that fully embraced automation did not just improve output; they redefined industry itself. Early adopters of mechanized production scaled exponentially, while those that took an incremental approach, adding machines without rethinking their operations, gained little and eventually disappeared.

The same pattern defines the AI era. Companies that rapidly and completely integrate intelligent automation into their core workflows will set new performance baselines.Those that treat AI as a bolt-on feature will struggle to compete against systems designed around it from the start.

Technology revolutions do not reward caution. They reward conviction. The lesson repeats across centuries: incremental adoption maintains the status quo, while rapid adoption reshapes it.

Jason Eubanks is the CEO and co-founder of Aurasell, the AI-native go-to-market platform built to unify CRM, automation, and intelligence in a single, agentic system. He has over two decades of experience in sales leadership and enterprise software innovation.