Helen Bevan

Why AI adoption is largely a psychological & cultural challenge, rather than a technology challenge.

I’ve just read the new book by @Gleb_Tsipursky, “The Psychology of AI Adoption at Work” as it’s one of the first books that offers in-depth advice about AI-enabled change through a human, rather than technology lens (& because I read his article on middle managers & AI in @HarvardBiz). The book describes itself as “a step-by-step tested guide for overcoming the biggest bottlenecks in AI adoption: human psychology & organisational culture.”

Some of the book’s key messages:

1) People talk about levels of “AI maturity” in organisations but there is no maturity curve. AI keeps evolving so there’s no end point. Adoption is a capability that needs constant renewal

2) Don’t underestimate the emotional & cultural side of AI-enabled change. AI touches identity; It automates writing, analysis & creative work that people see as part of who they are. Loss aversion, status quo bias & an empathy gap in leaders all shape the response

3) People support what they create. When frontline teams get involved in building their own AI tools, ownership lowers resistance, speeds up feedback loops & keeps capability inside the organisation

4) Engagement should be tailored. People hold different stances on AI & need varying responses: clarity on jobs for those fearful, data for the pragmatic, easy starts for the indifferent

5) Middle managers are key. They connect strategy with daily work & see the opportunities for change others miss. Hands-on experience of tests of change, peer mentoring & “premortems” help them lead with confidence.

6) Embrace sceptics – they make the work better. We should put sceptics on governance committees & get them to test AI tools for weaknesses before they go live.

7) Measure across several dimensions & frame measurement as learning. Time saved on its own is a misleading metric. One study found 36% of managers wasted more than half the time AI freed up for them

My main critique is that the book calls itself a playbook, but it offers approaches, not plays. The tools you would need to put them into practice (diagnostics, templates & worked methods on how to run each step) aren’t in the book. The introduction asks readers to build an adoption plan, guardrail map & KPI dashboard as they go, but it doesn’t provide templates or worked examples. In addition, the book would be strengthened if it pulled from established change & improvement methods, e.g., engagement frameworks, Plan-Do-Study-Act cycles & approaches to spread & scale.

I appreciate the content of this book. Its core insights are strong & important, from an author with a wealth of AI adoption experience. AI adoption IS change work. The principles that make any large-scale change initiative succeed also apply here: ownership, having a voice, psychological safety & learning as we go. Our challenge is to turn these principles into everyday practice.

Useful links for this post
The book:
Tsipursky G. The Psychology of AI Adoption at Work: From Resistance to Results. Georgetown University Press, 2026: disasteravoidanceexperts.com/aibook/#preord…

Companion resources referred to in the book: disasteravoidanceexperts.com/aibook

Gleb Tsipursky interviewed about the book by Toby Corballis for the Wicked Problems podcast: wickedproblems.fm

The original article I read from Harvard Business Review “Middle Managers Will Make or Break AI Adoption”: hbr.org/2026/09/middle…

Why does optimism matter in times of deep uncertainty & how do we keep it alive in our teams?

In our sector, many teams face long periods of uncertainty: financial & operational pressures, restructuring, changing policies, shifting priorities & job roles. Creativity & bold ideas shut down. Conversations turn to what might go wrong next. Pessimism becomes a shield against false hopes. Teams slip into learned helplessness, the state people enter “when they conclude their actions can no longer change the outcome.” This kills productivity & performance.

@MichelleGielan describes this pattern in her new @HarvardBiz article “How Leaders Counter Pessimism in Trying Times”. Her answer is “resilient optimism”: the ability to see challenges clearly while believing our actions can make a difference. At its core is agency, the sense that we can act & influence outcomes, whatever the circumstances.

It has to be realistic. Optimism “won’t fix a broken strategy or an unsafe workplace,” but it can shape whether people “disengage and wait, or stay in problem-solving mode long enough to find the next move.”

The impact is significant. Her team has tested more than 25,000 professionals in large companies, healthcare & education. Those with the highest work optimism are 3 times more likely to be highly engaged, 40% more likely to be promoted within 12 months & 5 times less likely to burn out.

As leaders, we shape our teams’ mood & optimism through tone, body language & small actions. In a University of Pennsylvania experiment, fundraisers briefly thanked by their manager made about 50% more calls the following week.

Practical actions to build resilient optimism in our teams:

1) Choose what you pay attention to. Teams read their leaders closely. Focus on purpose, progress & positive signals: thanks from a service user, a problem a team has solved. Every change effort produces progress that goes unnoticed. Making it visible is part of leading change.

2) Name the reality, then the next move. The author borrows “yes/and” from improv: “We have lost funding for this programme... & here is how we can protect what matters most for patients.”

3) Prioritise visibly. When everything feels urgent, ask: What can I step out of? What can I hand off with support & guidance? What am I doing out of habit or guilt? Leaders who show this discipline give teams permission to do the same.

4) Create positive dots. Tell someone what you noticed about their work & why it mattered. Ask a colleague what small thing would make their next step easier, then provide it.

5) Model recovery. Optimism requires energy. Talk about breaks & weekends as part of sustainable performance.

Resilient optimism starts with seeing the problem clearly, which optimists & pessimists can both do. What separates them is agency: whether we believe our next step can make a difference. The leadership work is what happens next.

The article:
hbr.org/2026/11/how-le…
In addition:
“Build the Mindset That Keeps Your Team Moving Forward”, HBR Executive Masterclass with Michelle Gielan
hbr.org/2026/10/build-…
and a podcast with the author: "Optimism Is Now an Essential Leadership Skill" hbr.org/podcast/2026/1…

I paired this with a graphic by Dr Hayley Lewis @Haypsych.

How do we believe change happens in systems?

One of the most positive moves in change practice in our sector is a shift towards “systems change”. By this we mean identifying & addressing the causes of problems in the system rather than treating their symptoms.

Often, we start by identifying methods & approaches for our systems change initiatives. As we build our practices in this area, we should dig deeper. We need to reflect on our “mental models” about how we undertake systems change. This means the beliefs & assumptions we hold about how change happens, shaping what we notice, what we expect & how we act.

I’ve been thinking a lot about this recently, as a result of an international improvement initiative I’m involved in. If we want to make big, positive changes happen in the world, do we start by identifying areas for collective action & “leverage points” for change? Or do we start by building the relationships & connections that create the conditions for change to emerge? By being explicit about our mental models & assumptions, we avoid the risk of different partners in the change operating with conflicting, unspoken views about how systems change and can align all our change activities (strategy, methods, reporting etc) around agreed ways forward.

I have found an article by @JewlyaLynn & Julia Coffman very helpful for my own thinking (all links in comments). They describe two mental models in systems change. “Systems dynamics” assumes a system’s main patterns are predictable. Our change strategy here targets high-leverage points with a theory of change & defined outcomes. “Systems emergence” assumes new patterns grow from the relationships between people. Our change strategy here brings in new voices, builds trust & learns alongside partners.

Neither model is better. Some parts of a system are predictable & others are in flux, so many strategies use both. Problems can start when the models get mixed unnoticed. The most common mismatch is emergent work held to systems dynamics accountability. Boards tend to favour clear predictions & quantitative metrics.

Russ Gaskin sees the same pattern. Initiatives speak the language of co-creation while using consultation methods, & the people involved never come to own the work. Systems maps & theories of change keep their value when they become a starting point for conversation.

Three reflections from me:
1) Whose mental model sits at the centre matters. When leaders impose their own view or process of change on the people closest to the work, they reinforce the power dynamics they set out to shift.

2) Our reporting mechanisms carry a mental model. When the strategy is emergent & the Board asks for predictions, the reporting pulls the work back towards prediction.

3) Naming our mental models is part of the work. Teams that make their assumptions visible can align strategy, methods & reporting with the system for better outcomes.

Links:
Lynn J & Coffman J. Passing in the Dark: Making Visible Philanthropy’s Hidden and Conflicting Mental Models for Systems Change. The Foundation Review, 2024;16(1):142-60. doi.org/10.9707/1944-5…

See also a shorter piece these authors wrote on the same topic: evaluationinnovation.org/publication/sy…

Gaskin R. The Emergence of Dialogic Systems Change. Horizons of Change, January 2026. horizonsofchange.substack.com/p/dialogic-sys…

We know that culture change programmes can create the conditions for health & care organisations to be more “change ready”, but what does it take for a culture change programme to become the way we work organisation-wide?

Natalie Wilson & colleagues have published a scoping review in @JBI_EI on embedding organisation-wide culture change programmes in health & care. They screened 7,922 studies but only included 17. One is a review I co-authored with Cynthia Willis & colleagues in 2016, so I read this with particular interest.

The authors separate 3 phases. “Implementing” gets interventions into practice. “Sustaining” keeps the programme & its outcomes going, usually 2 to 6 years after implementation. They also describe a middle phase, “embedding”, when change becomes part of the everyday routines of individuals & teams & part of organisational systems. The evidence for “embedding is particularly lacking.

10 factors emerged. “Education & training” & “measurement, monitoring & feedback of outcomes” appeared in every study. “Processes & structures”, “leadership”, “resources” & “cultural alignment” appeared in 16. “Shared, defined accountability” in 15. “An adaptable programme” in 11, “stakeholder engagement” in 8, “alignment with the external environment” in 7.

There is a tension in the design of culture change interventions. Should we initiate a programme that seeks to change culture "directly" through values, attitudes & messages? Or should we seek to change culture "indirectly" by redesigning the daily work, norms of collaboration & routines? It doesn’t say so explicitly, but the conclusions of this article are in the latter camp (as am I generally).

Five implications for leaders of change:
1) Build the change into daily work: Integrating new practices into existing tasks & duties, aligning them with current processes & accounting for the effect on workload.

2) Write it into the organisation’s routines. Reporting systems, governance, people processes, policies & monitoring are where a programme becomes business as usual. 7 studies pointed to defining roles & responsibilities in organisational policy.

3) Support embedding as its own phase. 9 studies named a dedicated budget as a key factor, alongside people & time to do the work.

4) Put new practices into induction & refresher training, so it survives turnover of people.

5) Share leadership across professions & levels, keep it steady & feed outcomes back so people see what the change achieves.

This review shows us how thin the evidence base on organisation-wide culture change interventions in health & care is. All 9 empirical studies focused on nursing. Patients took part in 2. Administrative & corporate colleagues are missing from the research. Culture appears as both the goal & a condition for success. The studies measured whether the programme became embedded, not whether the culture shifted. This knowledge is much needed & there is work to do.

Link: ovid.com/jnls/ijebh/ful….

Just a reminder that I'm hosting a webinar with Caroline Webb at 4pm UK time today. We will be discussing her new bestselling book Leadership Intelligence. During the webinar, we will discuss the leadership principles that are behind the book. I love the practical tools and frameworks for leaders that the book covers so I will ask Caroline to take us through some of my favourite ones. There will be time for questions and answers.

The session is aimed at leaders in health and care but the learning is generic so it's open to all leaders who want to improve their leadership practice. There is still time to sign up: events.teams.microsoft.com/event/7bf8a831…

I hope to see you there.
Helen