tey bannerman on why AI strategy is the new essential skill for design leaders

REDEFINING DESIGN LEADERSHIP IN THE GENERATIVE ERA

‘The industry isn’t dying, but the version of design leadership that existed five years ago is no longer sufficient,’ says Tey Bannerman, opening our conversation with him exploring the macro shifts reshaping the creative world. For Bannerman, design leadership in the age of AI is no longer simply about mastering the production of pixels, it’s about becoming the strategic bridge between technical possibility and human reality.

A former partner at McKinsey & Company and a trained software engineer, Bannerman argues that as the production layer of design becomes increasingly automated, the value of human capabilities has never been higher. Ethical judgment, contextual understanding, and systems thinking are now essential leadership skills. As he prepares to lead the ‘AI Strategy for Design Leaders’ — the newest course offered by the iF DESIGN ACADEMY, part of the prestigious German nonprofit design institute, iF Design — Bannerman aims to move the industry beyond surface-level AI hype. Offering a practical framework for understanding true organizational readiness and the often-misunderstood economics of AI adoption — this course models how to critically evaluate genuine innovation and protect creative integrity.

all images courtesy of iF DESIGN ACADEMY

IF DESIGN ACADEMY TRAINS STRATEGIC THINKING IN AI education

Kicking off on Thursday, June 18 and delivered in three 90-minute modules over one week, the iF DESIGN ACADEMY is addressing a clear gap in the market. The live online program equips design leaders with the frameworks and language they need to navigate AI transformation with confidence.

Delivered in three 90-minute modules over one week, participants work with Bannerman and cohort peers to develop the critical thinking skills required to evaluate AI pitches and learn from what has and hasn’t worked in the past. The intensive course curriculum culminates in a personalized 30-day action plan so learners return to their teams ready to implement effective workflows.

Tey Bannerman

IN CONVERSATION WITH TEY BANNERMAN ON AI TRANSFORMATION

The rapid shift in the industry raises fundamental questions about the future of creative work. Bannerman shares how leaders can reposition themselves as translators between technology and people, how to spot early warning signs of failure, and how AI can be used to amplify human judgment rather than replace it.

designboom (DB): How has the design industry changed since AI went mainstream?

Tey Bannerman (TB): The most significant change is in the fundamental economics of design work. When generative AI can produce competent visual outputs, the production layer is compressed, exposing the difference between design as execution and design as strategic thinking. We are seeing a bifurcation: an explosion of high-volume, low-cost AI output on one side, and a growing premium on human capabilities — contextual understanding, ethical judgment, and problem framing — on the other.

DB: For those stuck in the ‘AI vs. Human’ debate, how can we shift that mindset?

TB: The ‘AI versus human’ framing is ultimately unproductive. Historical revolutions show us that the printing press didn’t kill storytelling, and the camera didn’t kill painting — it liberated painters to explore what photography couldn’t capture. When a leader uses AI to compress research synthesis, that freed-up time should be used for the deep strategic thinking they never previously had space for. The ‘versus’ framing dissolves when you see AI as a restructuring of where your expertise matters most.

DB: How does a true AI strategy differ from simply learning how to use the latest software?

TB: Software training gives you capability, but strategy gives you the judgment to deploy it wisely. Strategy is understanding how AI reshapes your entire operating environment — your team structures, value proposition, and competitive positioning. Because the tool landscape changes monthly, a tool-centric approach means you are perpetually catching up. A strategic approach provides a stable framework to evaluate which work to automate, how to maintain quality under compressed timelines, and how to ensure outputs reflect the cultural and emotional nuances users care about.

DB: What are the most common strategic problems you see design leaders struggling with when it comes to implementing AI?

TB: Three patterns repeat. First is the tool trap — investing in tools without a framework for when and why to use them. Second is a positioning problem — designers have expertise in human behavior and trust but lack the vocabulary to frame these contributions strategically, leading them to be relegated to the aesthetics layer. Third — is the failure to distinguish between AI that augments human capability and AI that replaces it. Leaders must be involved in the strategic framing, not brought in later just to make an interface look presentable.

DB: What are the distinctly human parts of the design process that you think will become more valuable?

TB: When everyone has access to powerful creation tools, the value of creation itself declines. What rises is discernment — knowing what’s worth creating in the first place. Value is migrating toward three areas: systems thinking (synthesizing insights across cultures), moral reasoning (ethical judgment in ambiguous territory), and relational intelligence (building genuine trust with those affected by design decisions). These aren’t ‘soft skills’ — they are the hardest skills to master and the primary differentiators for strategic leaders.

DB: What red flags should leaders look out for in AI initiatives?

TB: Based on over 30 AI implementations, I see three consistent red flags. The first is starting with technology rather than a specific problem — if the brief begins with “we need to implement AI,” you’re likely building a solution in search of a problem. I’ve watched organizations spend millions on systems that sat unused because nobody verified that the problem actually mattered to the people affected.

The second is success metrics that only measure efficiency — cost savings, speed, or headcount reduction. These metrics incentivize automation when augmentation might be the better approach, and they completely miss the trust dimensions that determine long-term adoption.

Finally, there is the absence of domain experts — when initiatives are driven exclusively by technical teams without input from those who understand the day-to-day reality, you get systems that look elegant in a demo but collapse on contact with actual human behavior. The ultimate red flag is treating AI as a deployment exercise rather than a transformation journey involving behavioral change and cultural adaptation.

DB: What is the biggest untapped potential you see for AI in design right now?

TB: The biggest potential is the role design leaders can play in making AI work better across every domain. Most AI implementation failures aren’t technical, they’re human — wrong problem, wrong context, wrong assumptions. These are design failures. We are in a narrow window of opportunity where design leaders can bridge the gap between AI’s promise and its practical implementation. The ‘AI Strategy for Design Leaders’ course at the iF DESIGN ACADEMY is built to provide the frameworks to lead when the stakes are highest.