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      May 1, 2025

      Unlock the Power: Practical Steps to Making AI Work for Your Business

      SPM Mythbusters Series

      4 min read

      Written by: Jason Kotlinski
      Key Takeaways
      • Understand AI is not a magic bullet; success requires a clear focus on business value.
      • See why boosting individual productivity with AI is good, but only if it translates into tangible business gains.
      • Harness strategic resource allocation and thoughtful governance, which are crucial for maximizing AI's potential.

      AI is the hottest topic in tech, promising to revolutionize everything from customer service to product development. But amidst all the hype, it's easy to get lost in the weeds. How do you make AI work for your business, without falling victim to unrealistic expectations?

      Beyond the buzzwords: Focus on business value

      The biggest mistake organizations make is implementing AI for the sake of it. Before you invest a single dollar, ask yourself these questions: What specific business problem am I trying to solve? What are my company's goals for the next five years and how can AI help us achieve them? The "AI strategy" needs to have a purpose or it's just a waste of time.

      Productivity vs. profitability

      AI can undoubtedly boost individual productivity. It can help developers write code faster, marketers create more engaging content, and customer service reps resolve issues more quickly. But increased productivity is meaningless if it doesn't translate into tangible business gains.

      Faster coding is great. But what if there's no backlog? What if the team can finish projects earlier and there's nothing to do? It might be an increase in outputs, but what business value has it provided?

      The limits of language

      AI excels at generating human-like text, but it doesn't actually understand the meaning behind the words. It recognizes patterns and produces grammatically correct sentences, but it lacks genuine comprehension. This means you can't rely on AI to make strategic decisions or provide nuanced insights.

      It may sound great and feel compelling, but, without original ideas, the tool is useless. This means current AI is best suited for tasks that involve language-based summarization, data generation, and the like.

      Governance and resource allocation: The unsung heroes

      One of the most overlooked aspects of AI implementation is governance. How do you allocate your AI resources effectively? Who gets access to which tools? How do you measure the ROI of your AI investments? Without a clear governance framework, your AI initiatives are likely to become fragmented and ineffective.

      How much AI do you have? How much does it cost? What's its processing capacity? And who gets to use it? Without answering these questions, resources will inevitably be wasted.

      AI: A team player, not a lone wolf

      AI should be viewed as a tool to augment human capabilities, not a replacement for human workers. Instead of focusing on eliminating jobs, think about how AI can empower your employees to be more creative, more efficient, and more effective.

      Instead of replacing programmers, a new role may emerge, called "AI Agent Manager," that is dedicated to managing AI systems.

      Stop chasing hype, start driving results

      AI has the potential to transform your business. But it requires a strategic approach, a clear focus on business value, and thoughtful governance. Employ these key principles:

      • Define your objectives: What specific problems are you trying to solve with AI?
      • Focus on outcomes: How will AI impact your key business metrics?
      • Embrace governance: Who gets access to which AI tools? How do you measure ROI?
      • Prioritize collaboration: Foster communication between IT, finance, and business units.

      By following these steps, you can cut through the hype and leverage AI to drive real, measurable results for your business.

      Tag(s): ValueOps , Clarity , Strategic Portfolio Management , SPM

      Jason Kotlinski

      Jason Kotlinski serves as Product Manager for Clarity with clients all across the globe. He is responsible for customer-facing aspects of product management, leading development of key marketable features, and assisting senior management with backlog prioritization and new feature definition.

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