As the lynchpin of digital innovation, artificial intelligence holds the future for every forward-leaning business. But while AI and generative AI pave a path toward opportunity, they come with financial sustainability risks that can threaten the durable use of these technologies.
Unpacking this issue requires understanding AI’s addiction to the cloud. AI relies heavily on cloud storage and computing powers. Separate, they are nothing, but together, AI has velocity.
Cloud infrastructure and applications give advanced analytics, hyper-automation, and large language models the fast, scalable delivery channels they need to be effective. But this also triggers cloud expenditures that can go unforeseen and undetected. The Wall Street Journal recently published an article on how AI is impacting the ability to control cloud costs. Hidden infrastructure and application costs pile expenses on an already tricky cloud dynamic:
- Prices are rising for infrastructure and applications.
- Cloud services dominate IT budgets and IaaS invoices can spin out of control.
- Most companies are already spending more on cloud than they budgeted.
GenAI is driving another layer of technical debt for many businesses.
When you factor in AI’s costly yet indispensable ally with the high demands for new GenAI tools, it’s easy to see why investment strategies can quickly become financially unsustainable. GenAI is driving another layer of technical debt for many businesses. Under the pressures of constant innovation, we could see the AI cloud grow at new, record-breaking speeds. As these factors come together in 2024, we may even see cloud hangovers of the past three years grow into full-fledged AI-cloud bankruptcies. Hidden costs have the potential to bankrupt AI innovation because they limit the ability for CIOs and CFOs to create new budgets, finding funding from within as a means to sustain the economic cycles of digital transformation.
Investments in AI become untenable when costs outpace the value delivered or the growth of the business overall. One of the most significant innovation pitfalls is failing to account for contributing costs, including the underlying network platform and expertise needed to support AI. Returns must cover fully loaded expenses without increasingly consuming more of the IT budget — not to mention the IT staff’s time.
To keep disruptive technologies from disrupting financial futures, executives must navigate the adverse economics of innovation, drawing more attention to the sustainability of emerging technologies.
AI’s financial watchdog: Lean portfolio management
Research from Gartner shows that by 2025, “70% of digital investments will fail to deliver expected business outcomes due to the absence of strategic portfolio management.” Sometimes referred to as IT business management, the practice of technology portfolio management executes an innovation strategy while staying within the confines of financial and human resource constraints. To be resilient in their ability to innovate, companies should consider these key focal points.
Dispel misconceptions: AI automation means less to do but more to manage
Yes, AI automates operations, leading to productivity gains. However, it’s essential to acknowledge that investments require a paradigm shift in expense management. On-demand cloud resources and variable pricing structures offer favorable pay-for-what-you-use terms and infinitely scalable costs amid increased consumption habits.
Financial leaders should tighten their grip with visibility, control, and predictability in mind when investing in dynamically scalable technologies, as these are the guideposts for ultimately driving sustainable innovation.
- Look closely at your returns. Accelerated ROI (return on investment) can be achieved by closely aligning AI to business goals, prioritizing projects with quick wins, and regularly assessing the impact of AI on metrics. These are critical in attaining business value faster.
- Control and track both direct and indirect costs. Cloud financial management strategies, including FinOps, put governance in place with spending thresholds and proactive alerts. They also monitor all-in costs using chargebacks to connect expenditures to innovation projects and business lines to better trace results.
- Use AI to counterbalance AI’s side effects. While AI can spur more cloud expenses, it can also help control them. Advanced cost management platforms can find sources of overspending in multi-cloud environments and pinpoint the most cost-effective infrastructure configurations, making changes automatically.
Address friction points: Bring finance and tech together to cultivate accountability
Speed of innovation is a must, but as companies open the taps on AI, spending becomes decentralized, which makes cost control more difficult. Inherently, executives, line-of-business leaders, and employees want purchasing power, but financial checks and balances are necessary for risk management. CEO mandates can clash with risk appetites. This tension can create internal resistance and contention as innovation leaders are under increasing pressure to transform digitally. In contrast, financial leaders need to balance controls to tune spending continuously.
- Align tech and finance leaders and their teams under the assumption that AI and cloud spending will grow in ways that call for more collaboration, visibility, and real-time controls.
- Just-in-time approaches can help make the necessary mental shifts, constantly matching resources to demands with a commitment to rightsizing and reducing waste.
- Foster a culture of accountability, ensuring that financial responsibility permeates IT while digital innovation permeates finance. Rather than viewing innovation as individual projects, it should be seen as a broad enabler where sound personal investments facilitate continuous widespread advancements.
Affording AI transformation with minimal impact
AI’s addiction to cloud computing conceals a financial sustainability challenge that creates another impetus for guarded rationalization. The escalating impact of AI on cloud costs, the looming threat of “cloud inflation,” and the demand for GenAI raise concerns about unforeseen expenditures and AI’s ability to afford positive business outcomes with minimal impact in the near- and long-term.
AI promises unprecedented business growth, but companies must take charge of their tech portfolios to avert the risk of AI-cloud bankruptcies in 2024. Managing expenses and fostering a culture of accountability are crucial strategies. By aligning innovation with financial responsibility, businesses can capitalize on the limitless potential of AI without compromising their ability to transform reliably. Extending the useful life of AI will help extract more business value while also putting less pressure on innovation leaders.