August 11, 2023
Product Management

From Utopia to Dystopia: What the Internet's Rise Tells Us About AI's Potential Impact on Product Strategy

Around 2000, when "Terminator 3: Rise of the Machines" was playing in movie theaters, there were polarizing views about the future that the world wide web (“Skynet” in the movie) would bring humanity. Some had a utopian belief that the Internet would create an egalitarian society free from government control. On the other hand, the dystopian view forecasted increased surveillance, cybercrime, loss of privacy/individuality, and a "hive mind." Twenty-something years later, we realized both perspectives had some level of truth and were not mutually exclusive. During these years, we saw how the internet evolved from the initial gold rush through the “.com bubble”, where the only companies that survived were those with strong business models, a clear path to profitability, and products with sustainable competitive advantages.

Today, when we talk about Artificial Intelligence, the "dystopian" belief is that Skynet became a reality, that AI will take over humanity and end civilization. In contrast, "utopians" believe that AI solves humanity's problems. I have an optimistic view of AI, but I am not utopian. AI's economic and social impact will be exponentially more significant than the internet's impact during the last 20 years, both in creating new opportunities and in transforming or even destroying jobs and industries. It will bring “creative destruction” to a whole new level.  I do not think anyone knows the exact timeline of that impact, which will undoubtedly impact your product and customers. As a product leader, you must be deliberate about your AI strategy. Any proposed AI investments should have a clear market and customer impact, the right business model, and a solid understanding of the risks.

Some generic steps below may help you draft your AI strategy. Note that those steps are not linear but iterative:

  1. Understand your target markets, trends, and the primary market problems to solve.
  2. Look at what your competitors and companies working in adjacent markets are doing.
  3. Draft a product strategy that aligns with your company vision, target audience, main customer problems to solve, the company's appetite for risk, and investment. If your proposed strategy does not align with the corporate strategy, work with your executive team to find alignment.
  4. Until now, I have not mentioned AI in the steps; it is all about the problem to solve and not about the technology used to solve it. Now that you have identified the most critical issues, you must understand how much and what AI technologies can solve those problems (no or minimal AI might be an ok answer for your product, or the answer might be a full product and business model revamp). AI is just another tool at your disposal, and the investment should be analyzed based on the expected business impact.
  5. Refine your proposed strategy by working with cross-functional teams to validate potential impact, competitive advantage, and business model; ensure a high-level understanding across stakeholders; and identify the right technologies, risk appetite, tradeoffs, investment, timelines, and ROI.

In conclusion, product leaders must be deliberate about AI in their product strategy. It would be best to embrace AI simultaneously with caution and a clear understanding of the risks and market. As a product leader, it's your responsibility to identify the most critical problems to solve and determine whether AI is the right tool for the job. Finally, remember to align your AI strategy with your company's vision, target audience, and risk appetite, and focus your value proposition on solving market problems rather than just using AI. By following these steps, you can leverage the power of AI to transform your product strategy and stay ahead in today's rapidly evolving market.

For further reading about AI, check out:

Juan Illidge is the Director of Volunteer Staffing at the Boston Product Management Association. Juan has forged demonstrable product success for startups to large multinationals across multiple industries like lead intelligence, sales engagement, data, identity access management, legal tech, and telecom. His product experience expands Latin America, Europe, Asia, and the North American markets.