Reflections on an Autumn at the Other AI Frontier
And 12 small steps for leaders to take
I feel deeply privileged. I get to be part of the first meaningful conversations that hundreds of people have about AI.
I get to see the contorted faces as people witness the capability of AI technologies for the first time. I get to hear the gasps as people hear about AI-related harms. I get to watch rooms of people start off polarised in their viewpoints on AI, move towards an equilibrium as the conversation deepens. I get to see organisations have huge wins, and grapple with deep challenges. And I get to hear loads of great use-cases and collect lots of interesting data.
I also get to see how difficult it is for leaders who find themselves at this new AI frontier. School leaders, charity directors and small business owners, all wear many hats and have significant pressures. The arrival of AI can feel like yet another drain on their time. But the reality is, with a few simple leadership actions, it is possible to get the ball rolling on your AI journey, and your teams the power to innovate, be more creative and save time. And leaders are using AI technologies to free up their own time and help them through knotty situations.
We are calling this the ‘Other AI Frontier’. This is where organisations and their leaders encounter AI technologies for the first time. This blog series exists to share some of the learnings we see along the way.
Over just the past couple of months
We've worked with leadership teams at huge national-scale organisations and supported small businesses with purpose-driven missions. We’ve helped charites from household-names to the smallest 3-person teams, to think deeply and mindfully about how they use AI technologies responsibly.
In schools, we have run training for over 500 staff, run introductory sessions with ~200 school leaders and are part way through intensive 5-module cohorts with 40 school leaders at different academy trusts.
What is clear is that there is significant change afoot. For many organisations, there is external change (how do we adapt to other people using AI?) as well as internal change (how do we help our teams to be innovative with this new technology?). We know this scale of change is difficult for leaders.
Insights from the Other AI Frontier: 12 observations from the last 2 months
This particular blog post aims to capture twelve key themes that we see at this ‘Other AI Frontier’. Eventually each will have a more detailed post of its own. But in the interest of urgency, I’ve suggested a small next step that leaders can take on each:
1. Three Types of Organisations and the need to set intent: We’ve noticed that organisations response to AI can broadly be categorised into three types:
The ‘Yet to Engage’: Those who have thus far, for whatever reason, avoided or ignored engaging with AI technologies.
The Treadmill Runners: Organisations that are using AI to automate, getting leaner and more efficient, but not necessarily innovating.
The Gardeners: Those who adapt to the changing environment and are actively planting the seeds of innovation, supported by great cultures.
Simple Leadership action: Decide on your intent. Which type of organisation do you want to lead? Communicate this to your teams.
2. Usage is Growing but Uneven: We’ve come across many people who getting real value and significant productivity gains from using generative and non-generative AI tools. But uptake remains uneven. Across the organisations we've surveyed, about a third of staff have never used a generative AI tool. However, the error bar on this is wide—some organisations have seen nearly universal adoption.
ChatGPT remains the most popular Gen AI tool, followed by Copilot and Gemini, with bespoke AI tools popular especially in education. Awareness of others, like Perplexity and Claude, remains minimal.
Simple Leadership action: survey your team to understand their use of generative AI technologies, because…
3. The Security question and the risk of inaction: We see organisations with ambitions for a "Copilot-only" or "Gemini-only" approach in order to mitigate security fears, who discover that many staff members are already using other tools, creating a significant change challenge.
Simple Leadership action: Speak to your IT team and move quickly to provide guidance for your staff on the acceptable use of generative AI technologies when it comes to data security.
4. Understanding Team Sentiment: Time and again, leadership teams don’t have a clear understanding of how their staff are using AI or how they feel about it. There is immense value in simply surveying teams to gather insights and in leading exploratory conversations about AI’s role.
Simple Leadership action: Set aside 30 minutes for a conversation with your team about their use of and feelings about the use of AI technologies in the workplace. Embrace the vulnerability, accept that you won’t have all the answers, what you hear will be fascinating.
5. AI Literacy and the right language is the gateway to transformation: Understanding some of the real basic things about AI can go a huge way. The kind of stuff you can get across in about 30 minutes can really help unlock people’s understanding, and enable them to think through decisions around the benefits and risks of different types of AI for different situations. Make the basics simple for people and they often take their own learning journey from there.
Simple Leadership action: Share some great content on this. I still love Henrik Kniberg’s introduction to generative AI a great 17 minute watch. You could always also find the right person to provide a balanced introduction to AI (*cough!)
6. Friction and Learning: AI technologies are great at reducing or removing friction in processes. But we also know that this friction is necessary for learning. This is not just relevant to education but also applies to entry-level jobs. We had some fascinating conversations with organisations who are proactively choosing not to automate certain processes in order to ensure staff continue to develop essential skills.
Simple Leadership action: Ask ‘what do your people need to learn?’ and make sure that AI isn’t being used to automate away the learning opportunities.
7. Culture Eats Strategy for Breakfast: Creating the right cultures in organisations is the quickest way to drive innovation. Most of the immediate Generative AI wins are at an individual level. The quickest way to scale this is to get people sharing. Additionally, as AI tools become more integrated into daily work, organisations will need to establish new norms. How do we feel about AI-generated meeting summaries? Or AI avatars attending meetings on behalf of someone? What about AI-generated email exchanges? These are questions that need answers as AI tools - and especially AI agents - become more prevalent.
Simple Leadership action: Set up a meeting or a teams channel where people can share great AI use cases, or air their ethical concerns. Guide conversations to establish norms around particular uses such as AI note takers in meetings.
8. Considering the Broader Impact: Charities and schools, in particular, need to think beyond their own use of AI. They must consider how the use of generative or non-generative AI tools by others will affect the communities that they serve. This broader perspective is often missing from current conversations.
Simple Leadership action: Step back. Explore how other people using AI technologies could impact the community, customers or clients that your organisation exists to serve. How might this change your mission?
9. AI Arms Races everywhere: We see numerous examples of what could be described as an "AI arms race" situation, where two parties on either side of a decision are using AI tools, often to ‘game’ the other. This dynamic is visible in a range of situations, from children’s homework, to job applications, to grant funding. These arms races are often counter-productive and resource intensive. They are also where particular risks around fairness, integrity and equity lie.
Simple Leadership action: Identify the potential AI arms races around you. Where do you need to intervene to make sure decision making is fair, equitable and high quality?
10. The Energy (and water) question: ‘How do we square use of AI with our climate change goals?’. We get variations of this question in almost every organisation we work with. It’s a difficult one, particularly with the limited data available to the general user. But there are some principles and approaches that organisations can and are taking,
Simple Leadership action: Open the conversation with your team. Explore in relation to your organisations and your personal values. Seek lessons that you can learn from your approach to other policies that have to balance organisational efficiency and climate change impact (eg a travel policy). Challenge your team on the value you get from different AI uses.
11. Doing More, but with Purpose: Again and again, we hear that adopting AI tools should allow us to do more. But more of what? The best organisations we’ve seen are those that are transparent about what "more" means for them, in some cases organisations are making this ‘more’ personal time as an incentive for productivity.
Simple Leadership action: Ask “what would you like your team to be able to do more of?” and then ask your team “What would you like to do more of”. Use this to give your AI adoption a purpose from which everyone stands to benefit.
12. The opportunity and risk for inclusion and equity: Used well, AI technologies have huge potential to support inclusion. Almost every session I run, someone puts their hand up and says ‘I’m dyslexic, working alongside AI has been a game changer for me’. Teachers can differentiate material for their full range of students with ease. Yet we also hear of organisations penalising the use of AI in job applications. And then there’s the potential for bias and unfairness, especially where generative AI is applied to decision making.
Simple Leadership action: Challenge whether your team’s use of AI technologies is making your workplace more, or less inclusive.
Summary
These ‘simple next steps’ fit into two broad categories of action:
Conversations you need to have
Reflections you need to make
They require you to draw on leadership skills that I’m sure are already in your armoury: Leading powerful conversations when you don’t know all the answers; and being able to step back and see the bigger picture.
I would add one more thing, which is ‘get to know the tools yourselves’. As Ethan Mollick reflects: “a key factor in successful AI adoption is whether the executive team actually experiments with AI to try to get work done themselves. Those who do tend to feel urgency and push for transformation”. There are some great use-cases for leaders, like using Generative AI voice tools to help you think through (and maybe role play) a difficult conversation that you have coming up. Or more traditional AI tools that allow you to get insights from your data that you never thought possible. Or the ability to quickly turn short-hand notes into a summary of key events for your team.
It can feel daunting, but simply by leaning into some powerful conversations with your team, and taking a bit of time to reflect on where and how AI technologies are already showing up, it’s possible to make a lot of headway on your AI Journey
We know this is a challenging space for leaders. If you have the intent to lead for transformational change, we exist to give you and your teams the confidence to do so responsibly and ethically, whether you’re leading a school, business or charity.
Get in touch today to find out how we can help.