How to Accelerate Your AI Adoption

Everyone is telling you how to use AI – including people who have no idea how AI works.

AI adoption is tricky because,

• It is a technology that most people don’t understand.

• The current LLMs are new to most people.

• There is uncertainty about how much the output can be trusted, and what that means for workflows.

• People are uncertain about how best to use it.

• AI is rapidly evolving – what is true of today’s AI might not be true of AI in two months, let alone a year, or two years.

Does it actually make people more efficient overall? Does it reduce cycle time in people’s work? Are there some areas in which it can completely replace people, and other areas in which it cannot?

The answers to these questions are, respectively, (1) it depends, (2) it depends, and (3) yes.

This makes AI adoption a complex problem. By the term “complex”, I am referring to the differentiation between “complicated” and “complex” problems: complicated problems are understood but execution is difficult because there are so many moving parts; complex problems are not well understood, and there is no systematic way to decompose them into separate steps to solve them.

AI adoption is a “complex” problem, not a “complicated” problem.

To solve a complex problem, effective leadership is needed at all levels. People need to be mostly autonomous – otherwise they will not solve problems creatively – but too much autonomy results in things not getting done. It is a balance. Leader behaviors need to promote an innovative culture: one in which people share ideas and try things.

What does not work is directing everything from the top, like a big rollout. That will seem to succeed: you will meet milestones; but the results will be poor. The resulting capabilities will be off – not effective. That’s because people did not learn along the way, or if they did, they kept quiet and kept their head down, and met the milestone decided for them by their boss, who is trying to meet the milestone imposed by their own boss, who in turn is trying to meet the milestone of their respective boss.

The secret to being successful with something complex like AI is not to treat it as a fully planned-out project: instead, treat it as a goal. Define a vision, consisting of a set of objectives, such as “our customers are using our AI features and love them”, or “we are using AI to get our work done much faster”.

Allow the vision to morph over time.

Challenge people to solve objectives: ask them how it can be done. Talk it through and co-create strategies.

Carve out initiatives to implement the strategies, but define success in terms of the outcomes (e.g. “key results”) – not in terms of tasks done.

And don’t micromanage those initiatives.

In other words, it is “how we do things”. That’s behavioral.

Frequently ask for feedback: are these even the right objectives? Have we learned more, and do we now realize that our objectives should be adjusted?

That pattern of defining objectives, co-creating strategies, and delegating execution with success defined by results is a key pattern that should be replicated at all levels of the organization.

In other words, it is “how we do things”. That’s behavioral: leaders need to know to not micromanage. They need to know how to co-create in a way that encourages creativity and sharing of opinions. They need to know how to ask questions in a supportive rather than intimidating way, questions such as, “do we now realize that our objectives should be adjusted?”

The secret to being successful with something complex like AI is not to treat it as a fully planned out project.

We also need incentives that encourage those forms of leadership – incentives that don’t pit leaders against each other, because if leaders are overly competitive, then they will not voice true opinions when they are in a team meeting with others at their level: they will be more concerned with optics than with truth.

We can help people to learn to lead this way. We have studied companies that do. And we ourselves have amazing track records of successful leadership.

We also have tools that can help. We developed a planning and execution tool that supports working this way: instead of a task-based system, or a separate “strategy module”, we built an integrated system that creates obvious line-of-sight between mission/purpose → objectives → strategies → initiatives → capabilities to create → goals for those capabilities.

Using that tool, one cannot work without knowing what goals one is trying to meet, what capabilities the goals are for, what strategies the capabilities support, what objectives those strategies are for, and how those objectives support the mission or purpose. The connections are obvious, for everyone.

That’s important, because it gives people a feeling of agency: they know why they are doing what they are doing – they are not just toiling away at a task. They have a sense of purpose, and they feel encouraged to be creative, since it is about achieving the goal – not completing a task.

This shifts the psychology, which shifts the leader behavior : instead of being task status checkers, leaders become concerned with outcomes.

This shifts the psychology, which shifts the leader behavior: instead of being task status checkers, leaders become concerned with outcomes. They become inquisitive: “What’s in the way of achieving that goal?” instead of “How done is your task?”

But leaders need leadership development. Most people don’t receive leadership training, so it is no wonder that most are poor leaders. That’s a killer when you are trying to solve a complex problem.

The path to success is (A) upskill people’s leadership skills, and (B) provide tools that support and encourage effective leadership, rather than task tracking.

We can help.

And by the way, we understand how AI works – we have built AI systems from scratch, and we are in the process of adding a truly useful AI-based feature to our tool – a feature that cannot work without AI and that does not currently exist in the market. But this article is about how we can help you to go fast and adopt AI in an innovative and effective way. And ironically, it’s all about people – at least it is now, and will continue to be until AI can do our highest brain functions, which it cannot yet.