{"id":51067,"date":"2025-12-29T07:00:14","date_gmt":"2025-12-29T12:00:14","guid":{"rendered":"https:\/\/www.demandgenreport.com\/?p=51067"},"modified":"2025-12-15T12:52:59","modified_gmt":"2025-12-15T17:52:59","slug":"demand-gen-report-2025-reflections-aurasells-jason-eubanks","status":"publish","type":"post","link":"https:\/\/www.demandgenreport.com\/demanding-views\/demand-gen-report-2025-reflections-aurasells-jason-eubanks\/51067\/","title":{"rendered":"Demand Gen Report 2025 Reflections: Aurasell\u2019s Jason Eubanks"},"content":{"rendered":"

When Implementing AI, Don\u2019t Repeat the Mistakes of the Past<\/strong><\/em><\/h1>\n

Why GTM leaders must rethink how they adopt AI, not just which tools they choose<\/strong><\/h3>\n

Marc Benioff recently sounded the alarm<\/a> on artificial intelligence (AI) innovation outpacing customer adoption. But the real issue isn\u2019t speed. It’s anxiety.<\/p>\n

Every vendor now claims to be \u201cAI-powered,\u201d 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<\/a> they\u2019re adopting AI, only 10% are fully executing on those strategies.<\/p>\n

That gap is troubling but familiar. I\u2019ve seen this movie before back when the first generation of cloud GTM frameworks arrived.<\/p>\n

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\u2019ll again miss the chance to use AI\u2019s full potential to drive productivity, predictability, and efficiency across every B2B sales organization.<\/p>\n

AI implementation can\u2019t 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.<\/p>\n

Identify Subtractors, Not Add-Ons<\/strong><\/h3>\n

The first principle of AI adoption should be consolidation.<\/p>\n

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\u2019s the wrong instinct.<\/p>\n

Before you deploy any AI solution, ask: Which existing tools will this allow me to eliminate \u2014 or prevent me from buying later?<\/p>\n

AI\u2019s 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\u2019s subtraction by intelligence.<\/p>\n

We don\u2019t need more software. We need smarter systems that absorb complexity instead of compounding it.<\/p>\n

Focus on Productivity, Not Just Insights<\/strong><\/h3>\n

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.<\/p>\n

AI shouldn\u2019t just predict outcomes. It should restore time and elevate execution of humans.<\/p>\n

Predictive analytics that tell you what might happen are table stakes. Intelligent systems that automatically act on it\u2014 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\u2014 that\u2019s transformation.<\/p>\n

When evaluating AI for your GTM team, ask:<\/p>\n