How To Manage Expectations From Executives In AI/ML Projects

“How do we set and manage expectations from executives when implementing AI/ML solutions?”

Many non-technical business leaders have heard a lot of hype about AI and machine learning, but they are not sure how AI adoption works in the enterprise. It’s easy to have blind spots when it comes to the technical challenges and implementation process.

It’s common to see competitors talking about implementing AI use cases, often in public, and wonder if our company is staying behind. Nobody wants to be disrupted, especially after seeing the now commonplace fall of multi-billion dollar companies who failed to innovate.

This sense of urgency and excitement can lead to a hasty decision to “get going” with AI/ML without developing a proper strategy and forethought about the AI adoption journey. This includes setting expectations and understanding what successful AI adoption looks like (check out my blog post titled, “3 Steps In Your AI Journey” for more information).

Buy-in from senior management is paramount. However, setting and managing expectations is equally important. As business leaders, we must understand that the path to AI adoption success will not be a straight line. Understand your team will:

  • Make mistakes and learn valuable lessons (these lessons become part of the “AI Manual” for your organization).
  • Learn better ways to do things as they go through lean cycles (best practices are also added to the manual).
  • Get stuck in the middle of a project (check out my blog post titled, “What To Do When Your Team Hits A Wall During An AI/ML Project” for more information).
  • Improve their technical skills as they encounter unforeseen challenges (this improves your company’s overall AI technical expertise).

Make sure senior management understands all of these different factors during the AI strategy phase and prior to getting started with technical implementations. This may involve some amount of coaching and leadership guidance (check out my blog post titled, “Getting Started With Enterprise AI” for more information).

Managing expectations throughout projects will be much easier once business leaders understand the AI adoption journey, the expected challenges, the inherent iterative approach based on lean methodology, and AI business fundamentals.

Furthermore, project status updates will make sense, challenges are not alarming but rather expected, and we know for sure that we are making progress towards our goals. All of these things will help minimize business leaders’ potential frustrations and anxiety when an AI/ML project ‘seems to be taking longer than expected.’

As an organization ramps up AI adoption speed and gains momentum, all subsequent use case implementations will have the added value of best practices and validated learning (make sure everything gets documented in the ‘AI Manual’).

If you need help to accelerate your company’s machine learning efforts, or if you need help getting started with enterprise AI adoption, send me a LinkedIn message or email me at info@carloslaraai.com and I will be happy to help you.

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