Optimize AI Investments for Long-Term Business Growth

Ensure sustained business growth and efficiency with strategies to maximize AI investments.

Don’t let AI investments follow the path of underperforming digital investments

Despite high expectations, a significant portion of digital investments have failed to deliver their anticipated returns. AI investments, much like their digital forebearers, are expected to drive productivity and efficiency gains. While the ramp-up of AI strategy-fueled investments is relatively recent and data on outcomes is limited, given the similarities between digital and AI investments, there is a risk that AI investments may also underperform. 

Compared to traditional investments, both digital and AI investments require a broader definition of benefits, some of which don’t show directly on the P&L. To maximize AI investments, Gartner recommends leveraging the available data signaling underperformance of investments in digital transformation and adopting emerging best practices.

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    For successful AI investments, enhance ROI metrics

    Adapt ROI evaluation frameworks for AI

    Traditional ROI models, like net present value and hurdle rates, often overlook nonfinancial returns, including strategic, operational and risk reduction impacts. To better evaluate investments in AI, update ROI frameworks to account for their overarching impact.

    Categorize AI investments for competitive advantage

    Group investments into three types: commoditized, enabling and differentiating. This helps avoid spending too much on basic capabilities that don't add long-term value and allows more funds for AI investments that boost competitive advantage.

    Implement a proof-of-concept funding model

    A proof-of-concept funding model lets organizations set clear progress checkpoints, allowing finance teams to support promising projects and quickly stop those that aren't working. Because AI development involves a lot of trial and error, it requires an iterative and flexible model.

    AI Investments FAQs

    Why don't AI investments always pan out as expected?

    Executives mistakenly expect efficiency gains from AI investments to lead to reduced costs; however, without a clear resource reduction or reallocation strategy, these cost savings don’t always materialize.

    How can companies make AI investments more successful?

    Update how you measure ROI, focusing on projects that give a competitive edge, and use a proof-of-concept funding model to ensure better results and smarter use of resources.

    What should companies consider when evaluating AI investments?

    Make sure your organization is AI ready by defining a clear strategy and preparing cybersecurity and data inputs. Focus on projects that offer a competitive advantage and use flexible funding models to adapt as needed.

    Drive stronger performance on your mission-critical priorities.