Context Is the New Currency: AI, Scrum, and the Future of Product Delivery

Why It Matters

AI is reshaping how products are built, turning context into a strategic asset and forcing firms to redesign governance, talent, and delivery models to stay competitive.

Key Takeaways

• AI reshapes product delivery, making context the new currency.
• Generative AI boosts developer productivity, but shifts bottlenecks to requirements.
• Professional services feel knowledge commoditization, prompting cultural change initiatives.
• Teams must prioritize governance and data quality to harness AI safely.
• Leaders should aim to deliver more, not just cut development headcount.

Summary

In this Scrum.org podcast, CTO Tony Hinckley of Avanad discusses how generative AI is redefining product delivery and the role of Scrum. He frames context as the new currency, arguing that AI‑driven tools are turning raw data and intent into actionable code faster than ever before.

Hinckley notes that AI’s impact has been unprecedented in his 35‑year career, accelerating from basic autocomplete to prompt‑driven code generation. While developers see line‑of‑code costs plummet, the real bottleneck has shifted to the quality of requirements, business analysis, and governance. Professional‑services firms feel the pressure as knowledge becomes commoditized, and Avanad’s own internal rollout illustrates both the opportunities and cultural challenges.

He cites concrete examples: Avanad’s early adoption of GitHub Copilot and Microsoft 365 Copilot, pilots with central government and education clients, and the rapid uptake of AI tools by product owners, testers, and architects. "The first time in 25 years work has been disrupted this way," he remarks, highlighting the speed of adoption across engineering and non‑technical roles.

The takeaway for leaders is clear: AI can amplify output, but only if organizations invest in data hygiene, guardrails, and a shift toward higher‑order activities like ideation and strategy. Rather than shrinking development teams, firms should reallocate capacity to design, market research, and continuous learning to capture the full value of AI‑enhanced product delivery.

Original Description

In this episode of the Scrum.org Community Podcast, Dave West is joined by Tony Hinkley, Chief Technology Officer for Avanade UK. Tony brings a rare combination of perspectives: seasoned engineer, Professional Scrum Trainer, and senior technology leader helping some of the world's largest organizations navigate AI adoption. Together, Dave and Tony dig into what AI is really doing to product teams, Scrum practices, and knowledge work at large. This is an honest, experienced, and energizing conversation about where we are, where we're headed, and what it means for everyone who cares about delivering value professionally and sustainably.

Key Takeaways

• AI has disrupted professional services more than almost any other sector because knowledge, the core asset of consulting and IT services, is rapidly becoming a commodity. That's a wake-up call for all knowledge workers.

• Scrum Teams are seeing real productivity gains from AI  but those gains have moved the bottleneck. It's no longer about how fast developers can write code. It's about the quality of intent, requirements, and context being handed to the tools.

• The principles behind Scrum haven't changed but how you implement them must. Your Definition of Done, for example, may now be enforced by an agent rather than a person. Are your standards clear and documented enough for that to work well?

• Specialists get significantly better results from AI than generalists. First-principles thinking, clean code habits, and a strong sense of what "good" looks like are more valuable now than ever, not less.

• Context is the new currency. Giving AI tools access to well-structured, well-governed organizational data and standards will unlock far more value than simply upgrading to the latest model.

• Leaders face a real choice: use AI to cut costs, or use it to grow. Tony's strong recommendation is to invest freed-up capacity into the parts of your product organization that have always been under-resourced, strategy, ideation, stakeholder engagement, and product thinking.

• Data governance isn't a dirty word anymore, it's a competitive advantage. Organizations that get serious about data quality, classification, and security will be the ones that get the most from AI. Garbage in still means garbage out, and the consequences are bigger than ever.

• Mid-market companies should pay close attention. AI is leveling the playing field in a meaningful way, giving smaller organizations the ability to punch well above their weight in product delivery.

• If you're feeling uncertain about your place in an AI-enabled world, start by embracing the tools. As Tony puts it: AI won't take your job, but someone who knows how to use it well might.