Stop Playing Defense: Put People at the Center of Your AI Offense

Corporate AI roadmaps still read like procurement checklists, another chatbot, a little RPA, a promise of head-count savings. That mindset explains why, even as 78 % of organizations now use AI in at least one function, most gains are incremental. Nearly half of service operations adopters report cost reductions, yet the majority save less than 10 %—hardly the stuff of competitive separation. hai.stanford.edu

The Blind Spot: People

Efficiency talk crowds out the single factor determining whether AI scales: humans who can wield it with purpose.

• Barely 39 % of employees using AI have received any company-provided training, and only 25 % of firms plan to offer gen-AI training this year. microsoft.com

• LinkedIn’s 2025 Workplace Learning data shows just 38 % of companies teach AI literacy, even though 82 % of senior leaders say their teams need new skills to collaborate with AI. linkedin.com

When talent isn’t upskilled, automation savings stall and revenue upside stays theoretical. No wonder McKinsey finds only 1 % of executives call their gen-AI deployments “mature,” meaning fully embedded in day-to-day workflows. mckinsey.com

The “Prompt Engineer” Myth

A cottage industry has tried to plug the skills gap with “prompt whisperers.” Yet 2025 analyses already label the role “practically obsolete” as models learn to interpret everyday language and domain context matters more than clever syntax. salesforceben.com

Upskilling entire teams in data fluency, critical thinking, and responsible AI use beats hiring a few prompt gurus who guard their magic words.

Death of the Lone Big Idea

Marketing has long glorified the lightning bolt concept. In an era where creative can be generated (or killed) in seconds, growth comes from systemic creativity—rapid, data-rich experiments that compound. That transformation again hinges on empowered people: cross-functional “fusion teams” who mix brand instinct with machine insight.

A Playbook for Offense

1. Unify the data substrate. Fragmented assets make AI shortsighted. Tools like mktg.ai pull creative and performance data into one layer so every model and marketer can work from the same view.

2. Invest in people before pilots. Shift 10 % of your AI budget from tooling to continuous learning stipends, internal academies, and “sidekick” programs pairing domain experts with ML engineers. The companies that have done this already see revenue impact: 71 % of AI users in marketing and sales report top-line gains. hai.stanford.edu

3. Measure upside, not just savings. Track incremental conversions, cycle-time compression, or new-product velocity metrics that reward offense.

Proof in Practice: Coca-Cola’s Create Real Magic

Coca-Cola didn’t start with cost-cutting; it launched an AI sandbox that lets thousands of designers co-create assets with GPT-4 and DALL-E. The result: fresh consumer experiences, new revenue moments, and a global talent pool suddenly fluent in AI. coca-colacompany.com The tech mattered, but the people, platform, open access, shared assets, and rapid feedback drove the breakthrough.

Seize the Moment of Disruption

Moments of disruption, uncertainty, and change are your chance to go on offense. Take that opportunity to change the things you don’t like. Defensive AI strategies make your P&L a little leaner. Offensive strategies make your business fundamentally different, harder to copy, quicker to learn, and closer to the customer.

The tools are ready. The cost savings are table stakes. The real question is whether you will still be playing defense when your competitors start running up the score.