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Every enterprise has access to the same models, platforms, and vendors. The harder question is whether they have anyone left who can tell those tools what good actually looks like.

In this episode, Raja Walia and Akande Davis break down why most enterprise AI investments are not failing on the technology, they are failing on the sequence of investment. They cover why the human layer underneath the infrastructure is the part that produces ROI, why the companies building AI are themselves hiring humans, and why an unowned agent in production is not a moat. It is a dependency that scales bad decisions faster than anyone can catch them.

Key topics covered in this episode:

• The infrastructure bet has a ceiling, and most enterprises sequenced the investment wrong. Leaders are spending on platforms, models, and agents while the data is not ready, decision rights are unclear, and ownership is ambiguous. Gartner projects a significant share of generative AI projects will be abandoned after the proof-of-concept stage, a clear indicator that the human layer underneath the spend is not in place.
• AI replaces junior-level work, not senior judgment, and the ROI math has been pitched against the wrong category. Content production, campaign builds, and report summaries are real value, but they do not justify the capex profile most boards have approved. Adobe’s 2026 Digital Trends Report shows 68% of organizations cannot demonstrate ROI on their AI investments. MIT and BCG research shows the majority of enterprise AI initiatives fail to deliver meaningful financial impact, because the pitch deck assumed AI would replace senior decision-making, and it does not.
• The companies who built the AI are the ones investing hardest in the human layer. Anthropic is hiring engineers. OpenAI is hiring BDRs and SDRs. The vendors selling the tools that supposedly replace people are the ones rebuilding the human layer underneath, because they know that is where the leverage actually lives.
• AI does not fix a weak human layer. It multiplies it. When agents run on top of an operating model with unclear ownership, ambiguous data, and no one available to correct in real time, the agents do not heal those problems. They scale them. Wrong decisions execute faster, ambiguity moves quicker, and the damage compounds autonomously before anyone catches it.
• Two enterprises with the same tech stack will produce completely different results, and the variable is never the tool. The differentiator is the clarity of ownership and the quality of the human layer assessing it. The moat is not the platform. It is who owns the operating model, and whether anyone can be reached when an agent makes a call that has to be answered for. Without that, you did not build a moat. You built a dependency.

Note: Signal & Stakes was previously published as Call It RevOps. The rebrand reflects a deliberate shift in the conversation, from tactical execution and operational how-tos to strategic decision making and the consequences that follow when senior leaders get it right or get it wrong. Same hosts, same honesty, different altitude.

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Signal & Stakes is a podcast for people who sit inside the decisions that shape how companies grow, compete, and survive. Each episode surfaces a real decision, the signal that was there, what was at stake, and what happened next. Not advice. Consequence.

Signal & Stakes is hosted by Raja Walia, CEO of GNW Consulting, and Akande Davis, VP of Operations at GNW Consulting.

Signal & Stakes is produced by GNW Consulting, a strategic marketing technology and revenue operations agency helping enterprise organizations make sense of their existing MarTech investments. Through the GNW Orchestration Framework, GNW Consulting helps companies connect board-level priorities to day-to-day execution, identify where AI creates leverage across go-to-market operations, and determine where human judgment should lead. Learn more.

Subscribe to Signal & Stakes on Apple Podcasts, Spotify, and all major podcast platforms. New episodes drop monthly. Follow GNW Consulting on LinkedIn for episode releases, show updates, and content on marketing technology and go-to-market strategy. Watch full episodes on YouTube.