University of Kwazulu-Natal

How To Maximize Roi On Ai In 2025 Ibm

Bonisiwe Shabane
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how to maximize roi on ai in 2025 ibm

Since the generative AI boom erupted in late 2022, organizations have raced to implement AI initiatives that enhance their business objectives. Leaders have been on the hunt for scalable AI strategies that streamline operations, inform data-driven decision-making, reduce costs and turbocharge product development. But though the hype surrounding AI implementation continues to surge, many organizations are finding that the return on investment (ROI) of their AI solutions is falling short. A 2023 report by the IBM Institute for Business Value found that enterprise-wise AI initiatives achieved an ROI of just 5.9%. Meanwhile, those same AI projects incurred a 10% capital investment1. So why are most businesses struggling to profit from AI-driven solutions?

And how can they achieve a better ROI in 2025? It turns out that having AI isn’t nearly enough. Some business leaders jumped on the AI bandwagon in a FOMO-driven, short-term impulse move to stay ahead of their competitors. Others envisioned enterprise AI as the business strategy hammer for every nail. Both groups forgot the importance of nuance and planning. “People said, ‘Step one: we’re going to use LLMs (large language models).

Step two: What should we use them for?’” remarked Marina Danilevsky, Senior Research Scientist, Language Technologies at IBM. Her comment is a warning to companies potentially falling into the same shortsightedness trap with AI agents in 2025. Achieving positive ROI on an AI transformation requires the inverse approach. Fortunately, there’s a sunrise on the horizon for businesses and artificial intelligence. It’s not only possible, but likely, to achieve measurable ROI gains when implementing AI systems correctly—when organizations let strong data quality and AI strategy take the lead. As I noted in my last post, many firms are struggling to achieve demonstrably ROI from their AI initiatives.

That post provided suggestions from IBM’s experience on how to be an outlier – how to identify and then deliver tangible business benefit from AI. In this post I will dive into specifics on which use cases and processes we focused on, as well as how value was derived – this includes details on the specific accrued benefits and... While these examples are based on IBM’s experience – they really aren’t IBM-specific—they’re relevant to every enterprise. At IBM our transformative use of AI spans four key use cases: Enterprise Insights – this use case focused on enhanced data integration, governance, and real-time analytics to improve collaboration and compliance across finance, supply chain, and facilities. Customer Support – this AI use case focused on streamlined our support by eliminating repetitive tasks, enabling 24/7 self-service, and upskilling employees with role-specific knowledge.

(Sponsored post) Business transformation is hard. So hard, in fact, that 84% of efforts reportedly fail. Why? Because too many organisations don’t know where to focus, how to scale, or how to identify the path to measurable value. In an era of tightening budgets and resource constraints, finding and executing the right product ideas has never been more critical. In this INDUSTRY 2025 Spotlight session, Matthew Certner, Head of Digital Product Engineering and Design for IBM Consulting, delivered a message on four habits to lead product transformations successfully.

Matthew opened by challenging attendees to reflect on projects that consumed months of effort, only to be met with low adoption or no ROI. It’s a common challenge for product teams: products launched without understanding user needs or with too much confidence in assumptions over evidence. The remedy? Focus, feedback, and flexibility. Matthew shared findings from a recent IBM Institute for Business Value study that surveyed 1,000 product engineering leaders. Despite the widespread excitement around generative AI, one in five teams still doesn’t use it across any stage of the product lifecycle.

Done right, an AI First Approach to Product Development can compress timelines and cut costs. AI agents are no longer experimental—they’re operational. But for many executive leaders, the results have been underwhelming. According to the 2025 IBM Institute for Business Values C-suite Study, only 25% of AI initiatives have delivered the expected return on investment (ROI), and just 16% have scaled enterprise-wide. These numbers reveal a critical gap between ambition and execution. The problem isn’t AI itself—it’s how it’s being deployed.

Success with AI agents requires more than enthusiasm. It demands a structured, transparent and business-aligned approach that balances experimentation with governance, and cost savings with long-term growth. So how can executives shift AI agents from pilot projects to real business value? By starting with the right mindset, grounding their strategies in cost-saving use cases, and architecting for scale and flexibility. One of the most common missteps executives make is starting with the wrong ROI lens. Many leaders aim for transformative, top-line growth from day one, but the most successful AI implementations often begin with cost savings.

Why? Because cost benefits are easier to measure, faster to realize and provide the foundational business case needed to scale. ARMONK, N.Y., Dec. 19, 2024 /PRNewswire/ -- New research commissioned by IBM (NYSE: IBM) found that companies surveyed are investing in AI for the long term, with a growing interest in using open-source tools to drive ROI... The study of more than 2,400 IT decision makers (ITDMs), conducted by Morning Consult and developed in collaboration with Lopez Research, revealed that 85% of respondents report making progress in executing their 2024 AI... The data also confirms that using open-source tools for AI solutions may correlate to greater financial viability: 51% of surveyed companies currently utilizing open-source AI tools report seeing positive ROI, as compared to just...

Nearly two-thirds (62%) of all respondents indicate they will increase their AI investments in 2025, while 48% are planning to leverage open-source ecosystems to optimize their AI implementations. For those surveyed companies not currently utilizing open-source, 2 in 5 say they plan to use open source for AI implementation in 2025. "As organizations begin to implement AI at scale, many are placing greater stock in success metrics such as productivity gains, in part because traditional hard dollar ROI benefits have yet to show up on... "Yet, companies continue to rapidly advance their AI strategies, with no sign of slowing down. Companies now recognize the value of defining specific use cases and optimizing AI projects. They are leveraging hybrid cloud strategies and open source to drive AI innovation and deliver financial returns."

Enterprises are ramping up AI investment, but with a greater strategic focus ARMONK, N.Y., May 6, 2025 /PRNewswire/ -- Today at the company's annual THINK event, IBM (NYSE: IBM) is unveiling new hybrid technologies that break down the longstanding barriers to scaling enterprise AI – enabling... IBM estimates that over one billion apps will emerge by 2028, putting pressure on businesses to scale across increasingly fragmented environments. This requires seamless integration, orchestration and data readiness. A new IBM CEO study shows that business leaders expect the growth rate of AI investments to more than double over the next two years, with most actively adopting AI agents and preparing to... Yet their pace of investments has led to disconnected technology – and only 25% of AI initiatives have achieved the ROI they expected.

IBM is combining hybrid technologies, agent capabilities and deep industry expertise from IBM Consulting to help businesses operationalize AI. "The era of AI experimentation is over. Today's competitive advantage comes from purpose-built AI integration that drives measurable business outcomes," said Arvind Krishna, Chairman and CEO, IBM. "IBM is equipping enterprises with hybrid technologies that cut through complexity and accelerate production-ready AI implementations." Artificial Intelligence (AI) is no longer just a buzzword—it’s a strategic imperative. Yet, despite the hype, most AI projects fall short of delivering meaningful financial returns.

However, companies that master six key capabilities report an impressive 13% ROI, proving that disciplined execution makes all the difference IBM’s study, conducted in partnership with Oxford Economics, surveyed 2,500 executives across 16 countries. It revealed that organizations progress through a continuum of AI maturity—from ad hoc deployments to strategic integration. By maturing across six core capabilities and embedding trust at every level, organizations can move beyond hype and unlock transformative value. Forthright Cyber offers a unified managed cybersecurity solution, delivering robust 24x7 SOC coverage across endpoints, networks, users, and SaaS applications. Our clients benefit from real-time security insights and comprehensive views of their attack surfaces, ensuring unparalleled protection.

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