Winning with AI: Lessons from Success
Why some companies scale with AI while others stall
Despite growing excitement around artificial intelligence, only a tiny fraction of businesses convert AI pilots into enterprise-wide performance gains. While 78% of companies report AI use, fewer than 1% achieve maturity and measurable transformation.
So, what separates the winners from the rest?
At Trippl, we examined six global examples of AI done right—from PepsiCo to Microsoft—and distilled the strategic moves that turned early efforts into scalable, measurable value. These aren’t just stories—they’re playbooks.
Six Lessons from AI Leaders
Six Lessons from AI Leaders
1. Start with High-ROI Use Cases
AI initiatives that deliver fast, measurable value tend to focus on:
- Customer support (faster resolutions, higher satisfaction)
- Forecasting and supply chains
- Developer productivity
For example, EXL Service drove a 21% revenue uplift and 20% cost reduction in retail by embedding AI into core operations. They partnered with NVIDIA to extend capabilities and emphasized domain-specific AI models.
2. Build a Data Foundation That Scales
Snowflake enabled ROI of 41% globally (and up to 44% in ANZ) by prioritizing secure, governed, and accessible data infrastructure. This created the backbone for successful AI implementation in finance, retail, and logistics.
The lesson? You can’t scale AI without scaling your data maturity first.
3. Put AI Where Work Happens
Microsoft didn’t ask users to adopt new tools—they embedded AI into the ones they already use. Outlook, Excel, and Teams now include Copilot AI features adopted by over 85% of Fortune 500 firms.
ANZ Bank took a similar approach with GitHub Copilot, seeing productivity gains and improved code quality from developers using AI natively in their IDEs.
4. Mandate Measurable ROI
PepsiCo only greenlights AI projects with clear ROI, and links AI progress to executive KPIs. This governance-first approach has made AI a strategic lever, not a siloed experiment.
The result: a culture of accountability and alignment between innovation and enterprise value.
5. Support the People Side of AI
The most successful programs didn’t just deploy tech—they empowered people.
A landmark study by Erik Brynjolfsson showed a 15% uplift in cases resolved per hour when generative AI supported customer agents. Junior staff, in particular, benefited from skill elevation and confidence gains.
Change management, training, and trust are the fuel that moves AI from promise to performance.
6. Move from Pilots to Portfolios
The scattered project approach is a dead end. Leaders like EXL and PepsiCo manage AI as a portfolio—with executive oversight, structured governance, and clear pathways from prototype to production.
If it’s not measured and managed, it’s not going to scale.
What This Means for Your Business
What This Means for Your Business
Across all six examples, a pattern emerges:
- AI works best when it’s embedded, not bolted on.
- ROI happens when success is defined, tracked, and tied to KPIs.
- Adoption accelerates when people are supported, not sidelined.
Whether you’re just beginning or looking to scale, the key is intentionality—designing AI into the way your business operates, makes decisions, and delivers value.
Final Thought
Winning with AI isn’t about chasing the latest tool. It’s about integrating AI into your business engine—where your people, data, and decisions meet.
And when done right? The results speak for themselves: productivity uplifts, smarter workflows, better customer outcomes, and ROI of 15% to 60%+.
Want to learn how we can help design your digital strategy for measurable enterprise value?
Contact our team at hello@trippl.co to start the conversation.
