As key in the field of digital innovation, artificial intelligence holds the future of all forward-thinking companies. But while AI and generative AI pave the way for opportunities, they carry financial sustainability risks that can threaten the lasting use of these technologies.
To solve this problem it is necessary to understand AI's addiction to the cloud. AI relies heavily on cloud storage and computing capabilities. Separated, they are nothing, but together, AI has traction.
Cloud infrastructure and applications provide the fast, scalable advanced analytics, hyperautomation, and large language models they need to be effective. But this also triggers cloud expenses that can be unforeseen and go unnoticed. The Wall Street Journal recently published an article about How AI is impacting the ability to control cloud costs. Hidden infrastructure and application costs pile up expenses in an already complicated cloud dynamic:
- The infrastructure and application pricing are increasing.
- The Cloud services dominate IT budgets y IaaS bills can get out of control.
- La Most companies are already spending more on the cloud than they budgeted.
When you take into account the onerous but indispensable ally of AI along with the high demands for new tools for GenAI, it is easy to see why investment strategies can quickly become financially unsustainable. GenAI is creating another layer of technical debt for many companies. Under the pressure of constant innovation, we could see cloud AI grow at new and record-breaking speeds.
As these factors come together in 2024, we may even see the cloud hangovers of the past three years turn into outright AI cloud bankruptcies. Hidden costs have the potential to derail AI innovation because they limit the ability of CIOs and CFOs to create new budgets and find internal financing as a means to sustain business cycles. digital transformation.
GenAI is creating another layer of technical debt for many companies
Investments in AI become unsustainable when costs exceed the value delivered or the growth of the overall business. One of the biggest obstacles to innovation is not taking into account all the expenses included to support AI, including the underlying network platform and the necessary expertise. The results of innovation must cover total expenses without consuming more and more IT budget, not to mention IT staff time.
To prevent disruptive technologies from disrupting the financial future, executives must navigate the adverse economics of innovation, paying more attention to the sustainability of emerging technologies.
The AI Financial Watchdog: Efficient Portfolio Management
A Gartner investigation shows that by 2025, “70% of digital investments will not achieve expected business results due to the absence of strategic portfolio management.” Sometimes called enterprise IT 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, resulting in productivity benefits. However, it is essential to recognize that investments require a paradigm shift in spending management. On-demand cloud resources and variable pricing structures offer favorable pay-as-you-go terms and infinitely scalable costs amid increased consumer habits.
Finance leaders should strengthen their governance by considering visibility, control and predictability when investing in dynamically scalable technologies, as these are the guidelines to ultimately drive sustainable innovation.
- Attention to detail in the returns obtained. Accelerated ROI can be achieved by closely aligning AI with business objectives, prioritizing projects with quick results and periodically evaluating the impact of AI on metrics. These are critical to achieving more immediate business value.
- Control and track direct and indirect costs. Cloud financial management strategies, including FinOps, implement governance with spending thresholds and proactive alerts. They also monitor total costs through returns of payments made to connect expenses with innovation projects and lines of business to better track results.
- Use AI to counteract its side effects. While AI can drive more cloud spending, it can also help control it. Advanced cost management platforms can find sources of overspending in multi-cloud environments and identify the most cost-effective infrastructure configurations, making changes automatically.
Addressing friction points: bringing finance and technology together to make accounts more efficient
The speed of innovation is essential, but as companies turn on the taps of AI, spending becomes decentralized, making it difficult to control the same spending. 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 appetite. This tension can create internal resistance and contention as innovation leaders find themselves under increasing pressure to digitally transform. Instead, financial leaders need to balance controls to continually adjust spending.
- Align technology and finance leaders and their teams under the assumption that spending on AI and cloud will grow in ways that will require more collaboration, visibility and real-time controls.
- The just-in-time approaches They can help make the necessary mental changes, constantly adapting resources to demands with a commitment to right-size and reduce losses or waste.
- foster a culture of responsibility, ensuring that financial aspects permeate IT while digital innovation permeates finance. Instead of viewing innovation as individual projects, it should be viewed as a broad enabler where strong personal investments facilitate continued, widespread advances.
Enable AI transformation with minimal impact
AI's addiction to cloud computing masks a financial sustainability challenge that creates another impetus for cautious rationalization. The growing impact of AI on cloud costs, the looming threat of “cloud inflation,” and demand for GenAI raise concerns about unforeseen expenses and the ability of AI to enable positive business outcomes with minimal impact in the short and long term.
AI promises unprecedented business growth, but companies must take charge of their technology portfolios to avoid the risk of AI cloud bankruptcies in 2024. Managing expenses and fostering a culture of responsibility are crucial strategies. By aligning innovation with financial responsibility, companies can capitalize on the limitless potential of AI without compromising their ability to reliably transform. Extending the lifespan of AI will help extract more business value while putting less pressure on innovation leaders.
