6 Keys To AI Adoption

Opening Thoughts

It’s hard to imagine having a conversation at work these days without AI coming up at some point. Two powerful letters that are now part of the modern-day lexicon, where, before too long, it will be like saying – “yes, I use the internet.” 

It’s a topic so broad and deep that, admittedly, it will be challenging to do justice to it in this writing alone. Thus, more articles and Clear Moves Consulting service offers, gleaned from our experiences working with AI companies over the last few years, are on the way and will be available soon. But here are six key considerations as you begin your AI adoption journey.

1. Cut Through the Noise

In reference to Murphy’s law #3 at the top of this article, begin by asking yourself four fundamental management consulting questions that underpin any new business initiative.

1. What are you trying to do?
2. How are you trying to do it?
3. What are your assumptions?
4. What if your most cherished assumptions were wrong?

Have a conversation with your leadership team, then with the broader employee group. Go around the room and brainstorm what people think Artificial Intelligence is, and encourage them to openly share their fears and aspirations regarding AI application in your organization. 

2. AI is Not a Strategy 

To start, it’s important to note that AI is not a strategy; rather, it is a highly effective technology-driven tool that sorts through data inputs and provides answers quickly. The needs organizations have for AI are like those they had when early pioneers like IBM and AWS first introduced cloud computing to the market. Cloud computing offers organizations and individuals options for storing and processing their IT functions. 

These incredible technological breakthroughs, while remarkable in every respect, support various objectives and supporting strategies and underpin activities that are part of the overarching strategic plan. For example, you can set an objective to have AI chatbots improve customer engagement by 30% in the following year. 

3. Push Past the Myths

The most common myth regarding AI is that it will take over a significant portion of the entire workforce. You would be right to assume that AI contributed to the creation of some parts of this article. However, it did not write the whole piece, as no machine can truly convey the human experiences I’ve had while working with AI companies over the past few years. Nor could it replicate my excitement regarding the topic.

Therefore, part of your AI readiness might be to create a mechanism to reassure your employees regularly that, while AI adoption is coming, the complete dissolution of the workforce is just media hyperbole. I can provide you with a reference from a Clear Moves Consulting case study. 

• A client of ours is a senior executive at an AI company responsible for securing and keeping global advertising projects on track. At times, his responsibilities include bringing together a dispersed workforce, including client managers and clients, in Europe and the US. The criticality of this exercise, having a human element, should not be underestimated. 

4. Assess Customer Impact

Peter Drucker, the legendary management consultant, aptly said: “The purpose of a business is to get and keep a customer. Profits result from running the business effectively.”

If you adhere to this theory, you need to consider improving customer retention, then work backward to the responsibilities expected of your employees. Keep in mind that AI’s impact will affect both individual and relational duties within the company. Across the board, you’ll see a shift in skills demand, requiring you to identify use cases by job function and then undertake the inevitable upskilling, along with defining the outcomes you want your AI platform(s) to achieve.

5. Identify Your Adoption Starting Point 

Begin with a thorough analysis to sort through what you think AI can and should do for your organization. Build an orderly critical path, find the starting point, analyze where you are, identify shadow AI, and break down the specific ROI goals. Consider:

• Data Collection: Streamlining the process of gathering and organizing data to improve efficiency and reduce manual effort.
• Customer Onboarding: Automating workflows to accelerate the integration of new customers, ensuring a smooth and efficient experience.
• Employee Onboarding: Simplifying the process of bringing new employees into the organization by automating documentation, training, and access provisioning.

6. Governance and Risk Management

Recently, I attended an executive breakfast where, by show of hands, only about 2% of the audience admitted that their boards had begun or developed an AI adoption strategy in concert with their leadership teams. Further panel discussions during the Q&A confirmed the importance of establishing governance models to address a myriad of issues, including cybersecurity and terms of use. 

Internal organizational governance will need to include issues such as managing 

who can access which tools, when, and to what extent, understanding IP ownership rights, and managing controls by line of business or centrally through IT. Externally, you’ll need to understand any current or potential AI use mandates from professional societies or industry regulators, such as the CRTC for Canadian Telcos. Either way, I recommend consulting legal experts as you progress along your AI adoption journey.

Concluding Thoughts

The organizations that succeed with AI will do so by creating an adoption framework that includes a disciplined critical path, prioritizes employee upskilling, and encourages ongoing dialogue with employees.