80% of AI projects fail
🚀 AI Projects: 80% Failure Rate? Not on My Watch! Imagine someone tells you your project has an 80% chance of failing. Would you even start? 😱 Well, here's the kicker: According to Harvard Business Review, a whopping 80% of AI projects DO fail. Ouch!
Throughout my 25 years of steering business transformations (yes I am that old 😃), I've learned that de-risking implementations isn't just about deploying technology—it's about cultivating a mindset of meticulous oversight and adaptive strategies. Here’s a distilled approach from my 20+ years of experience. It’s a simple three step process that will de-risk your AI and CRM programs, aligned with insights from thought leaders in the field:
Establish a Center of Excellence (CoE): centralize your knowledge
Creating a CoE isn't just a procedural step—it's about building a hub of wisdom. This center becomes the brain of your digital initiatives, where knowledge about e.g. AI applications and their intersections with business processes is centralized. Here, we don't just manage risks; we anticipate them, ensuring that every AI deployment amplifies your strategic objectives without overshooting your risk appetite… and the budget of course.
2. Maintain a Dynamic AI Inventory: avoid shadow AI
You don’t want to end up with shadow AI in the company and have critical data out in the open.
As someone who has seen technology evolve rapidly, I can't stress enough the importance of keeping a living inventory of all your digital applications applications. This catalog isn’t merely a list—it’s a strategic tool that details how and where we apply AI, helping us gauge its impact and align it with our broader business goals. Regular reviews and updates of this inventory ensure that we stay on top of potential risks and compliance needs, allowing us to make informed decisions swiftly. You don’t want to end up with shadow AI in the company and have critical data out in the open.
3. Embed Continuous Improvement and AI Governance by design: a new Operating model
The landscape of AI and its associated risks is ever-changing. Hence, adopting a robust framework for continuous improvement is crucial. This governance framework integrates risk management into every phase of AI implementation, fostering a culture where compliance, legal, and IT standards are not afterthoughts but foundational elements. Through continuous education and evolution of our practices, we ensure that our approach to AI remains both cutting-edge and secure.
These steps aren't just strategies; they are part of a philosophy that respects the power and also the risks in deploying AI technologies.
With the right governance in place, you will be able to tackle challenges such as data issues, complexity and scalability, access to skills etc upfront. Taking this proactive stance ensures that AI initiatives are in line with the business strategy and will deliver sustainable outcomes.
Curious how we can help you set up for success? Let’s connect!