The Digital Clinic

BUILD Lab is inviting you a different kind of industry evening built around your cases.

The Digital Clinic brings individuals working through the hard problems such as transformations that stalled, the platforms that overran, the AI rollouts that haven’t landed.

The evening is built around carefully matched roundtables, bring practitioners together with researchers who study exactly these problems.

Chatham House rule makes it an even playing field by respecting each other. You’ll leave with a sharper read on a challenge you’re wrestling with, and a room of peers and specialists worth staying in touch with.

Every attendee is asked to bring either a live challenge or a relevant past experience.

We will put you with your peers at roundtables making sure relevant experiences are covered and everyone can contribute.

Topics at the Roundtables

Future of Work

Perhaps the hybrid policies that aren’t landing, return-to-office rollouts causing attrition, reskilling with low uptake, workforce plans that can’t say which roles survive. How do you make defensible decisions when the evidence is contested and future of the workplace depends on it?

Hybrid policies that aren’t landing, return-to-office rollouts that triggered attrition, reskilling programmes with low uptake, and productivity measurement in knowledge work that produced numbers no one trusts.

What ties these cases together is that ways of working have shifted faster than the evidence base or the management playbook. The useful conversations are about making defensible decisions when the data is contested, the politics are loud, and the workforce is watching how you decide.

Digital Platforms Ecosystems
& Sourcing

Cloud migrations with eroding business cases, build-versus-buy on strategic capabilities, hyperscaler terms shifting underneath you, multi-vendor programmes where accountability slips. How much capability to keep inside, and how to govern the platforms you depend on?

Cloud migrations where the business case has eroded, build-versus-buy decisions on strategic capabilities, hyperscaler relationships with shifting commercial terms, multi-vendor programmes where accountability falls between the cracks, and insourcing after failed managed-service deals.

What links these cases is a deeper question: how much capability do you keep inside, how much do you push to platforms and partners, and how do you retain enough internal expertise to govern the vendors you increasingly depend on.

Human-AI Collaboration

Maybe copilot rollouts with uneven adoption, decision-support systems staff quietly override, customer-facing AI without working escalation, ML models that failed moving from pilot to production. How to design work so humans and AI each do what they’re genuinely good at?

Transformation programmes struggling to show board-level outcomes, innovation labs whose work isn’t crossing into the core business, digital portfolios where no one can say which initiatives are working, agile transformations that produced ceremonies without changing outcomes, and post-merger integrations where the value case is stuck.

What connects them is the gap between the language of transformation and the mechanics of actually changing an organisation — and the governance and measurement choices that separate the two.

Management of Digital Innovation
& Transformation

Or perhaps the transformation programs struggling to show board-level outcomes, innovation labs disconnected from the core, portfolios where no one knows what’s working, agile rollouts that changed vocabulary but not outcomes. What does actually shift an organization versus what only sounds like it does?

Copilot rollouts where adoption is uneven and value is hard to evidence, decision-support systems staff are quietly overriding, customer-facing AI where the escalation path isn’t working, and ML models that worked in pilot and failed in production.

What ties these cases together is a design question the industry hasn’t answered well: how do you shape work so humans and AI each do what they’re actually good at, rather than humans supervising outputs they can’t meaningfully check.

Schedule

15:30 – 16:00:  Arrival
16:00 – 16:05:  Introduction of the event
16:05 – 16:20:  Experience from Industry
16:20 – 17:20:  First round of roundtables
17:20 – 18:20:  Second round of roundtables
18:20 – 18:30:  Wrap-up
18:30 – 19:00:  Tapas and networking

Leave with a diagnosis on the painful projects you are OR have been working with.

Date: Sep 3rd, 2026

Time: 15:30 – 19:00 

Location: ITU, ScrollBar

IT-University of Copenhagen
Rued Langgaards Vej 7
2300 København S
Danmark