Driving adoption through empath
Unpacking a practical, empathy-led approach
Change works best when people feel seen. GenAI is no exception. The most effective rollouts do not start with tools or features. They start with curiosity, empathy and a genuine effort to understand how real people get work done. What follows distils a practical, people‑first approach to GenAI adoption in a complex, regulated environment, with concrete tactics you can reuse today. The focus is simple: help colleagues feel confident, protected and supported, so they actually use the technology and realise value
Why empathy accelerates GenAI adoption
A people‑centred approach starts by recognising that the job is not “rolling out a tool”. The job is solving for goals, pain points and motivations across different roles. That insight reframes the work. Instead of asking “how do we deploy GenAI”, you ask “what matters most to our teams, and where could GenAI relieve friction or create new value”
At one UK law firm, that mindset shift changes everything. An innovation lead who speaks the language of law, technology and business partners with change management to translate “the art of the possible” into relevant, safe and useful everyday practices. The team treats adoption as an ongoing journey rather than a launch day event, and it shows in the outcomes
The challenge with a tech‑first rollout
The first pass mirrors what many organisations try: a classic tech‑led rollout supported by an enthusiastic champion network of around 70 to 80 people, plus generic training and encouragement to “go explore”. Interest exists, but engagement lags. Champions ask the right questions: How is this relevant to my role. Where should I start. What does “good” look like in my world
Those questions are signals. They say the programme is missing context, not content. The fix is not more features. It is more empathy
A discovery‑first pivot that puts people at the centre
The team pivots to a discovery‑first approach grounded in human‑centred design. Before enabling access, they run short one‑to‑one interviews with department heads and practitioners. The focus is not the tool. It is the work. What does a typical day look like. What are the key responsibilities. What motivates you. Where do you lose time. What do you worry about
From those conversations they co‑create “Day in the Life” scenario maps that depict real activities and prompts colleagues can try immediately. The maps use language from the team’s world, which lowers cognitive load and builds confidence. After these interviews, one team sees Copilot usage increase by 700 percent in the following weeks, a clear sign that relevance unlocks behaviour change
Why it works
- People feel heard, so they lean in rather than opt out
- Barriers surface early, which allows you to mitigate them before they harden into resistance
- Discussions about value move from abstract to concrete, which creates momentum
What changes when risk and governance walk alongside delivery
Fear of hallucinations and data privacy does not disappear with enthusiasm. It must be addressed head‑on. The programme brings risk and governance in from day one, not as a late‑stage gatekeeper but as a design partner. Together they set clear guardrails and unambiguous policies that require human verification of GenAI outputs before anything client‑facing leaves the building. In a regulated context, that clarity is liberating. People know what is allowed, what is not, and how to use the tool responsibly. Transparency with clients about the use of GenAI strengthens trust rather than erodes it
Measuring value without losing the plot
Return on investment is a fair question. The team builds an adoption dashboard that tracks usage trends and prompts per day across departments, then pairs those metrics with qualitative feedback and time‑saving estimates. The goal is not to reduce people to numbers. The goal is to learn where value shows up, and where friction persists, so future improvements target the right problems. Success measures continue to evolve, in partnership with the vendor, as the technology changes and new patterns of use emerge
Innovation and change in tandem
Innovation and change management are complementary disciplines. Innovation expands the “what could be” through discovery and experimentation. Change management turns that into “what should be” through structured delivery, engagement and reinforcement. In practice the two roles overlap. The team embraces that grey space instead of fighting it. They run department‑by‑department “rings of release”, co‑design training with digital learning, and treat every rollout as a learning loop. Where responsibility is ambiguous, they solve it together, guided by a shared principle: do what helps people succeed
Sustaining momentum with simple, repeatable tactics
Adoption is not a moment. It is a rhythm. Several lightweight tactics keep energy high without overwhelming busy teams
Peer‑to‑peer micro‑stories
Short 30‑second videos from champions show specific, real use cases colleagues can copy that day. The clips run on internal screens and in comms to normalise usage and share tips from trusted peers rather than the project team
Live, hands‑on showcases
An annual technology and innovation week gives everyone a chance to try tools, ask questions and see demos. A recent summer fair version includes a playful “wheel of fortune” that reveals new Copilot features. Beyond the fun, these moments deliver learning at scale. Around 400 people attend; 94 percent say they learn something new about GenAI and technology, and 89 percent report improved awareness of how the tools can help their work
Open learning loops
Twice‑weekly drop‑in sessions with trainers create a safe space to ask anything. Champions help drive attendance and keep the conversation going between releases. The team continues discovery as a habit, not a phase, so they can adapt quickly when needs shift or features change
Key challenges in change management
- Explaining relevance to diverse roles in plain language
- Balancing enthusiasm with legitimate concerns about accuracy and confidentiality
- Measuring value credibly without turning adoption into a numbers game
- Avoiding tool sprawl in a regulated context where external LLMs are off limits for confidential data
- Meeting different expectations about pace across technical, legal and business stakeholders
Actionable takeaways
- Start with discovery interviews before you grant access, targeting goals, pain points and “jobs to be done”
- Convert insights into “Day in the Life” maps with ready‑to‑use prompts that mirror real work
- Invite risk and governance into the core team from day one and publish clear guardrails
- Build a small, motivated champion network with senior leader backing and capacity to contribute
- Roll out in rings by department to tailor examples and learn between waves
- Pair a usage dashboard with qualitative stories of value, then refine measures over time
- Use 30‑second peer videos to spread practical tips across the organisation
- Create recurring drop‑ins to answer questions and share what changed this week
- Keep experimenting with small, safe interventions so you can learn fast and iterate
- Treat innovation and change as a partnership that shares outcomes and flexes responsibilities
Benefits of further learning
If you want to see this approach in action, there is more to explore. You can watch peers describe their best Copilot use cases in their own words. You can see how “Day in the Life” maps make unfamiliar technology feel intuitive. You can dig into how risk and governance translate concern into confidence without slowing progress. You can hear how a discovery‑first mindset shifts the conversation from features to value. Most importantly, you can bring fresh, concrete ideas back to your own programme the very next day
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