Leadership
- Start with your senior leaders. In effect, you need to go through a managed change process with them first, to ensure they are all aware of the need for change, have a desire to implement it, and have the knowledge they need to do so. Your senior team has probably been through quite a few changes, but none of them will have gone through what you are going to experience with AI.
- Explain the business drivers making the use of AI essential. Don’t sugar coat this, but be mindful of not using “doom” scenarios. Your model should be Bill Gates’ “Internet Tidal Wave” rather than Stephen Elop’s “Burning Platform”.
- For every single communication, ask yourself whether it contributes to helping employees be able to think "I understand why this change is needed". If not, rethink that comms.
- Be clear and consistent in messaging – and have leaders deliver the message (but make sure they are clear about it themselves).
- Tailor your message. Customize communication for different groups within the organisation. Different stakeholders may have different concerns and questions, so addressing them specifically can be more effective.
- Inspire and engage your team members to participate in the AI adoption process.
- Identify and involve key influencers and champions who can advocate for AI and influence others.
- Highlight the personal and professional advantages of AI, such as learning new skills, increasing productivity, or advancing career opportunities.
- Create a sense of urgency and excitement around AI and its potential.
- Provide adequate and relevant training and resources for your team members to learn about AI and how to use it effectively. Make sure you document any process changes.
- Tailor the training to suit different learning styles, levels of expertise, and roles.
- Use a range of methods, such as workshops, webinars, online courses, or peer coaching.
- Encourage feedback and evaluation to measure progress and identify gaps.
- Support your team members to apply their AI knowledge and skills in their daily work.
- Create a safe and supportive environment where they can experiment, practice, and learn from mistakes.
- Provide guidance, feedback, and recognition to reinforce positive behaviours and outcomes.
- Make sure success stories are being shared, and that your teams are helping each other.
- Monitor and track performance and results to ensure quality and consistency.
- Celebrate and reward your team members for their achievements and contributions to the AI adoption process.
- Focus on improvements in employees’ experience, not just business benefits.
- Solicit and act on feedback to improve and refine your AI practices and policies.
- Reinforce the benefits and value of AI for your business and your team.
- Keep your team informed and updated on the latest AI trends and developments and encourage continuous learning and improvement.
How to roll out AI in a creative business
I talked recently about how changing the culture of learning in your business will be important if you will make the most of AI. But no matter what, you’re going to have to roll it out – and you need to do that in a structured way.
Remember, this isn’t just an ordinary technology roll out: it’s a change management process that will have a lot of impact on your business. One framework which can help, and that I have found incredible powerful for managing change at scale is the ADKAR model of change management.
This model consists of five stages: Awareness, Desire, Knowledge, Ability, and Reinforcement. Each stage focuses on a different aspect of the change process, from creating a clear vision and generating buy-in, to acquiring the necessary skills and (importantly) sustaining the change over time, something that’s often neglected.
So how might you use ADKAR when looking at an AI rollout?
Awareness
At this point, your focus is to communicate the need and benefits of AI for your business, such as improving efficiency, enhancing customer service, or gaining insights. Explain how AI aligns with your vision, strategy and values, and what challenges it can help you overcome. Use data and evidence to support your case and address any concerns or misconceptions.
Remember, too, that this stage is about the need for change, not that change is happening. The most important outcome for this stage is that everyone understands the “why”.
Key elements of building awareness
Desire
Building desire is all about cultivating willingness to support and engage with the change, and for AI, it’s incredibly important. While AI is a technology, it requires cultural change to succeed – and changing a company culture is very hard. Without building desire, any change which threatens the existing culture will fail.
There are many factors which influence whether you can create a desire for change. Personal circumstances will matter, and the fear with AI is that employees will lose their jobs. That’s a big barrier to building desire.
And, in some cases, those fears will not be misplaced, so it’s critical to be clear about your plans if you are to win enough trust to create desire. Consider, for example, making a commitment to reskill employees whose roles are affected by AI, rather than giving bland statements about avoiding redundancies “where possible”.
This is especially critical if you have a poor track record of managing change – so it’s vital that you are in touch with how your change management record really looks to your teams.
At this point, you should also identify your champions. Who, in the business, has a lot of influence? Who are the people who are at the centre of many things, who act as communicators? Who do other employees go to for help and advice? Are there people who, when a new project starts, are the first names on the list? They are not always senior, so make sure you’re looking across the board for your champions.
Even if they are not the most senior people or the most engaged with AI at this point, if you win them over and make them part of the project, you will reap the benefits.
Remember, too, that desire is personal to everyone. While making the business more efficient and profitable tends to get your senior team grinning, not everyone in your business is motivated by that. Focus, too, on the benefits for people’s careers, work/life balance, and especially with AI, freeing up time to do more creative things and less routine work.
And don’t, whatever you do, talk about how “if we don’t become more efficient, people will lose their jobs”. I’ve seen this approach taken many times, and in creative businesses, it almost never works. Desire is about motivating people to change, and fear is a bad motivator.
Key elements of building desire for AI:
Knowledge
If awareness is about the why, the knowledge stage is about the how: how are we going to use these tools? This is where you build knowledge of the tools and the processes by which you use them.
One mistake that I have seen made – OK, to be honest, I have made – is to focus too heavily on training people on how to use a tool, without also training on changes in the processes you’re expecting people to make. Every new tool, including AI, comes with processes changes. And, in fact, the process changes that the tool enables are where you achieve the biggest benefits.
Training people in the context of the processes they follow (and any associated changes) relates the training to what people do – and that’s why I would recommend role-based training, which may cut across teams. If you have large teams, consider further segmenting this according to levels of experience. But I would recommend that you train everyone if possible: people who are left out may end up feeling either that AI isn’t relevant to them (and it will be) or that they have no future in your new, AI-enabled business.
Key elements of building knowledge of AI:
Ability
So far, what we have done is all theory. This stage is where the rubber really hits the road because it’s where all that training starts to be implemented. And at this point, people will start to spot issues they didn't see before as they get the hang of new processes and get better at them. They will also find things you didn’t anticipate, and even better ways of using AI.
One aspect that’s critical at this stage is the generation of short-term wins. For a lot of your teams, AI is the proverbial big scary thing which is going to cost them their jobs – and even if you have had a successful “desire” phase, it can be easy for people to be knocked off course when that is at the back of their minds, or they are reading scare stories about how AI will mean the end of humanity.
Quick wins will help with this. They are positive, visible evidence about the success of people they know using AI, and in storytelling terms that is absolute gold dust. Remember, though, that the positives must be personal, and in a creative business they need to focus on improving the creative work. Shaving 10% of the time taken from a boring business process might be incredibly valuable to you, but it’s not all that compelling to a writer, editor, or video producer.
Key elements of building ability in AI:
Reinforcement
This stage focuses on activities that help make a change stick and prevent individuals from reverting to old habits or behaviours, and I think it’s both the most crucial stage of managing a change in technology or process – and the one that’s easily forgotten.
There are several reasons for this. First, commitment even among your senior team may be waning, leading to reduced encouragement from the top to continue along the path. The people who thought that your rollout of AI was likely to fail will probably be latching on to every bump in the road and turning them into roadblocks – ones that they “knew would happen”.
This is why it’s incredibly important to have all your senior team go through a parallel managed change process, to make sure they are all bought into what you want to achieve. AI is a strategic change on the same level of impact long-term as a complete restructure of your entire business, so there is no getting round managing that process for your senior team.
If you are starting to get resistance to AI deployment at this stage, check whether your senior team are still bought into it. In the worst case, some of them may be sending subconscious signals to their teams that they don’t have to keep going.
And now the bad news: in terms of budget, the reinforcement phase may cost as much as the training required in the knowledge phase because you need people looking after the AI roll out who are constantly engaging with your teams, understanding issues, celebrating success, and making sure that communications about how AI works for everyone, and – importantly – keeps everyone updated on new developments and changes.
For every new pitch, product or process, someone needs to be in the room asking how you can use AI to improve this, speed it up, or do interesting creative things. That is the only way they AI will become embedded in what you do, and not fade away – as so many corporate projects do.
Who is that person going to be? The likelihood is that in the “desire” phase, internal champions will emerge who can do that job. This offers the advantage of credibility, as it’s someone who is both personally familiar and professionally respected, but don’t make the mistake of assuming this role is something that you can tack on to a day job. Unless your business is very small, doing all this is a full-time role, for at least a year after you have “completed” the rollout of the technology.
Key elements of reinforcing AI use:
The continuing challenge of return to office
This is the first post-Substack edition of my newsletter, the first one delivered via WordPress. At some point in the coming days, the Substack version will be going away completely. If you want to know why, then you might want to read my post on Substack and platform risk, and then have a look at Platformer’s post on why it’s leaving Substack.
It’s just over twenty years since the last time I worked completely in an office. In every job, I have had since 2003 when I left MacUser, I have spent at least a day a week working from home. And even before then, working away from the office was so frequent that I doubt there was a week between 1995-2003 when I wasn’t out for at least a day.
Perhaps that’s one of the reasons I find the apparent desperation to get employees back into offices so strange. According to a survey by ResumeBuilder, 90% of employers plan to return to office by the end of 2024. Over a quarter of them intend to threaten employees who don’t want to return to office with being fired.
But return to office hasn’t been plain sailing. The latest company to come a cropper with its plans is Internet Brands, the parent company of WebMD, which created a video “encouraging” its teams back into the office, ending in a screen – and I am not making this up – which notes “we mean business” and “don’t mess with us”.
Cue much hilarity from the internet. Internet Brands is probably lucky that Twitter isn’t the force it once was because the pre-Musk social network would have run with this one for several weeks. Now, it’ll get buried under an avalanche of rubbish on Threads after a couple of days, or be seen by the couple of million users on Bluesky.
But I digress.
There are many arguments over the effectiveness of remote working vs in-office, some good and some bad. Having a separation between home and work is a good thing, for one, and although older employees tend to have plenty of space to make that work, younger ones in shared accommodation or living with parents often don’t. And younger employees also benefit from working closely with colleagues, who can mentor them informally much more easily when physically present.
I think this is particularly true for the creative industries. Creative people typically like to think of themselves as the definitive solo fliers, coming up with great ideas and then hammering them into shape, before having them ruined by an editor.
But the reality is that creative work is always collaborative. For example, in digital publishing, your content teams and audience development people need to mesh and work as one team; otherwise they can make the human equivalent of the sound gears make when grinding against each other.
And that is why broad directives about the amount of time which people spend face-to-face vs remote are damaging not only to the people involved, who inevitably feel robbed of autonomy and disempowered, but also to a creative business.
To find the most workable approach, leaders should focus on four factors: the needs of the work, the needs of the people, how work gets done, and the new managerial muscle required to manage a hybrid workforce.
Broad, uniform directives can only be effective if all work is identical and performed by a uniform workforce, which is not the case in the creative industries, and not true for most others. Rather than imposing directives, CEOs should empower their managers, particularly those at the front line, to develop a comprehensive understanding of their team's work, the working styles of their team members, and the most effective ways to accomplish their tasks.
Of course that depends on having empowered, well-trained leadership down to the small team level – but you are already doing that, aren’t you?