Driving Business Value with AI: 7 key preconditions

Will generative AI take your business to the next level? Casually exploring what AI is and what it can do is a good starting point. But that’s very different from truly assessing whether AI can generate real value for your organization — and what that would look like in practice.

In this article, Frieda van Belle, core faculty member of the Advanced Program Driving Business Value with AI, outlines the seven key preconditions for unlocking the full potential of AI and data in your organization.

Precondition 1: Understand how AI adds value to your business

Generative AI, like any new technology, is a tool you can use to create value in two ways:
• To enhance your value proposition, helping you serve your customers better
• To work more efficiently as an organization, enabling employees to deliver more value at the same cost

Are you confident AI brings no specific added value to your business? Then you don’t need to read further. After all, AI is a means to an end, not a goal in itself. Maybe blockchain, a drone fleet, or VR adds far more value in your case! But if you conclude that AI can contribute to your business, then it likely stems from improvements in fulfilling the needs of customers and/or employees — the two key sources of business value.

If you don’t define what you want to achieve with AI, it becomes a chaotic stew with no consistent value.

Precondition 2: A clear future vision of your business

Developing a vision of what your business could look like with AI in 5 to 10 years makes the difference between merely implementing AI and actually achieving success with it.
Imagine: How do you want to serve your customers in 5 to 10 years by doing XYZ?
The risk with AI is that you can apply it in a hundred different ways. Without a clear goal, it becomes a mixed bag with no coherent value output.

Precondition 3: A concrete overview of the gap between now and your future vision

To understand what needs to change within your business, you need a clear view of the delta between your current setup and your AI-driven future.
Think about people, culture, tech, cost, knowledge, skills, data, operations, etc.
Starting with AI productivity hacks like auto-generated meeting notes can be fun – but the real question is: What does the future look like?
Will virtual agents attend meetings for us? If not, you risk applying AI to processes built for the past, not the future — potentially a huge waste of time and resources.

Precondition 4: A feasible and actionable plan to bridge the gap

Once you’ve mapped the gap, you’ll need a concrete plan to bridge it.
This usually involves several projects on both the value proposition side and the organizational side — including, crucially, some knowledge and tooling projects.
These help your entire organization understand what AI is, what it can do, and how it could or should be used in your context.

Precondition 5: A learning mindset – start small, then scale up

As with any new tech, the best approach is to learn by starting small.
First, test your underlying AI hypothesis. Don’t begin with a core process — try it on a small subprocess using an off-the-shelf tool.
If the hypothesis holds up, you can scale — building working, learnable products that inform the next iteration.

Everyone wants to know: “What’s in it for me?”

Precondition 6: Future-proof governance – for both data and algorithms

If AI is becoming part of your business future, then governance needs to evolve too — not just for data, but also for algorithms.
What applies today only to financial data, will soon apply to all data.
If your data governance is a mess — even if you work with the safest AI partners — it’s like locking your front door with 28 bolts while leaving all the windows and the back door wide open.

Precondition 7: Attention for people

Change management is essential to bring people on board — and it starts with precondition 1.
Think stakeholder management and storytelling: everyone wants to know “What’s in it for me?”
Change management is especially critical when it comes to technical shifts. These are often surrounded by uncertainty, myths, and fear:
Can I still learn this at my age? Will my job still exist in 5 years?
Ultimately, the value you create with AI and data depends on your people — on how well you can engage them, spark their curiosity, and get them involved in solving real challenges that matter to both your workforce and your customers.

Curious how leading organizations are leveraging AI to generate real business value? 

Then the Advanced Program Driving Business Value with AI is the perfect next step for you. Immerse yourself in real-world business scenarios where AI and data analytics are the driving forces behind breakthrough decisions.

Discover the Advanced Program Driving Business Value with AI »

Webinar: The 7 Preconditions in Practice | May 22 at 12:30 PM

Curious how to apply these 7 preconditions in your own organization? On Wednesday, May 22 at 12:30 PM, Frieda van Belle will host a free webinar diving deeper into the practical implementation and answering your questions. Click here to learn more and register — and discover how to make AI truly impactful in your organization.