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Artificial Intelligence: Invest Now or Later

Updated: May 27

Artificial intelligence (AI) has the potential to revolutionize businesses, but deciding when to invest in the technology can be challenging. This article examines the advantages and disadvantages of investing in AI now versus later, and introduces a phased approach that businesses can use to incorporate AI.

The Pitfalls of the AI Hype Cycle:

Businesses often get caught up in the hype cycle surrounding AI. They see headlines about AI transforming industries and rush to implement it without a clear strategy. This can lead to unrealistic expectations and poorly chosen solutions. As described in the MIT Sloan Management Review (2023) [1], blindly following the hype can result in adopting immature technologies that haven't proven their value.

Companies have two main options when faced with new technology: be a pioneer or a fast follower. According to the Harvard Business Review (2022) [2], pioneers pave the way but face integration challenges and high costs. Fast followers, on the other hand, wait for the technology to mature and benefit from the lessons learned by pioneers.

However, there are drawbacks to both approaches. Pioneering can be challenging as it requires integration with existing systems, high upfront costs, and can result in encountering unforeseen technical difficulties. On the other hand, fast following can have its limitations. By waiting for the technology to mature, businesses may miss out on first-mover advantages. Additionally, mature solutions may have limited customization options.

Pioneering AI

Fast Following AI


  • First-mover advantage

  • Customization to business needs

  • Easier integration

  • Learn from pioneers


  • Integration Challenges

  • High upfront Costs

  • Potential unforeseen technical difficulties

  • Missing first-mover advantage

  • Limited customization

The Road to AI Success: A Phased Approach

So, how can businesses avoid these pitfalls and achieve success with AI? Here's a roadmap that incorporates a phased approach:

  1. Strategy Alignment: Before diving into AI solutions, clearly define your business goals. Align your AI strategy with these goals to ensure the technology directly addresses specific needs.

  2. Building Use Cases: Identify specific tasks or areas where AI can offer significant value. Focus on use cases with a clear ROI to demonstrate the tangible benefits of AI adoption.

  3. Organizational Readiness: Perform a Gap Analysis and assess your organization's infrastructure, talent, and data quality. Once you know where your business currently is situated from where you need to be in order to implement Gen AI, you can focus and build a plan to get your organization ready. Ensuring your IT systems can integrate with AI solutions and that you have the necessary skills to manage and maintain them.

  4. Agile Phased Implementation: Mitigate risk and optimize success with a phased approach while using a Scum Agile Methodology every step of the way:

    1. Pilot Program: A small group of users tests the chosen AI solution in a controlled environment. This provides initial feedback and helps identify potential issues.

    2. Departmental Rollout: The technology is deployed to a specific department, allowing for further refinement and user training based on the learnings from the pilot.

    3. Full-Scale Implementation: After successful testing and adjustments, the technology is rolled out to the entire organization.

  5. Nurturing AI ROI: AI is not a one-time investment. Continuously monitor and measure the performance of your AI solution. Refine it as needed to ensure it delivers the expected ROI.


By understanding the reasons why AI implementations fail, businesses can avoid the hype trap and adopt a strategic approach. A focus on c lear goals, well-defined use cases, and organizational readiness, coupled with a phased implementation process that acknowledges the trade-offs of pioneering and fast following, paves the way for successful AI adoption and a sustained return on investment.


  1. MIT Sloan Management Review (2023). When to Implement New Technology [invalid URL removed]

  2. Harvard Business Review (2022). Teaming Up to Crack Innovation and Enterprise Integration Teaming Up to Crack Innovation and Enterprise Integration 

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