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How do I know if it’s the right time to bring AI into my organization?

AI is here to stay

Whether we like it or not, AI is everywhere. Previously reserved for think tanks or startups looking for a buzzword to attract investments, we’re now seeing how AI can augment nearly every major industry. Like the lightbulb and the internet, AI is here to stay.

Microsoft CEO Satya Nadella says in his book, Hit Refresh, “Anyone who says they can accurately predict the future trajectory of tech is not to be trusted.” While he later says that a growth mindset continues to be beneficial, his warning rings true. Both the dot-com bubble in 2001 and the cryptocurrency bubble in 2018 are tangible examples of the risk of investing in tech based on speculation alone. However, these bubbles also teach a lesson; while emerging tech markets are typically over-valued, their innovations have real value. While it’s hard to say which “groundbreaking advances” in AI have substance, one thing won’t change: how to decide when AI’s right for your organization.

On your journey to discover if your organization can benefit from AI, I recommend taking a step back to reflect on the wisdom from those who came before us. Harvard professor and strategy expert Michael E. Porter published Competitive Strategy: Techniques for Analyzing Industries and Competitors in 1980. It has since been translated into 19 languages and serves as a “North Star” for many of the world’s business leaders. While the book’s tone and case studies may seem outdated in today’s fast-paced environment, the underlying lessons are gold for those willing to dig for it.

One nugget of wisdom Porter gives us is a seven-step framework, which he calls the “Elements of the Capacity Expansion Decision.” The title may sound daunting, but this framework provides a step-by-step process to analyze whether it’s time to invest in a new capability, which in this case is AI. You’ll find those steps below, along with some questions to help guide your AI investment decision.

1. Determine the firm’s options for the size and type of capacity additions.

a. How many resources (time, money, and people) can you invest in onboarding AI?

b. What does AI vertical integration look like for your organization?

c. What happens if it fails?

2. Assess probable future demand and costs of inputs.

a. Will this AI feature help you scale?

b. Will your competitor’s adoption of AI affect your market share?

c. Will the variable costs of these services decrease as the AI function scales?

3. Assess probable technological changes and probability of obsolescence.

a. Would your AI function be easily copied by other developers?

b. Does the function seem gimmicky, or will it really help your core business?

c. Does this function solve a problem that was predetermined by your team?

4. Predict capacity additions by each competitor based on the competitor’s expectations about the industry.

a. What is my competitor doing, and what do they expect me to do?

b. Is the industry starting to adopt AI?

c. Is the technology ready for industry adoption, or is this just a bandwagon to avoid being the last in?

5. Add these [four previous points] to determine industry supply and demand balance and resulting industry prices and costs.

a. Can I convert the answers to the questions above into tangible metrics?

b. Can I use these metrics and industry knowledge to accurately estimate the cost of adoption?

c. Am I being honest and checking for inconsistencies within my analysis?

6. Determine expected cash flows from capacity addition.

a. How do I measure the revenue generated from this AI adoption?

b. Will AI adoption increase variable revenue or decrease variable cost?

c. How long will it take to get the cash back on the initial investment?

7. Test the analysis for consistency.

a. Do I have enough time to run a pilot?

b. What metrics am I measuring in this pilot?

c. What do I do with the pilot results?

I encourage you to not get swept in the commotion when deciding if it’s time to make this big investment decision. Step away from the noise and listen to what your experience and research tell you. Socialize your ideas with trusted colleagues and don’t be afraid to bring in an outsider for a fresh take. There’s no way to predict the future, but if you are honest in your assessment and do your homework, there is a good chance your AI investment will be fruitful.


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