Generative AI adoption sets the table for AI ROI
Join leaders from Block, GSK, and SAP for an exclusive look at how autonomous agents are reshaping enterprise workflows – from real-time decision-making to end-to-end automation. As generative AI matures, the competitive advantage will go to those who embed it deeply and intelligently across their organizations. For banks and credit unions ready to move from hype to impact, this generative AI playbook provides a valuable guide. Banks and credit unions should treat each AI-enabled workflow like a capital investment—with clear ROI metrics, performance tracking, and continuous feedback loops.
Sophisticated participants improved their one-year performance by 9.6%, while less sophisticated ones saw only a 1.7% bump in returns. The authors note that “our results are consistent with generative AI amplifying pre-existing disparities in investment tasks by disproportionately benefiting more sophisticated investors.” Providing real-time data and predictive insights can help board members understand AI’s impact and make informed decisions. Emphasizing the competitive necessity of AI can motivate action while highlighting AI governance and trust can ensure scalable deployment.
For example, a company might implement an AI system to improve customer service without setting specific targets for improvement. Without targets, measuring the system’s impact on customer satisfaction or response times becomes difficult. A business might deploy AI to enhance operational efficiency but fail to establish KPIs like process completion time or error rate reduction, making it hard to assess the AI’s effectiveness. Founded by tech visionaries John Furrier and Dave Vellante, SiliconANGLE Media has built a powerful ecosystem of industry-leading digital media brands, with a reach of 15+ million elite tech professionals.
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Other areas include operations, tech support, human resources and customer service, Jyoti said. The first step to realizing GenAI’s true ROI is remembering that while this technology holds great potential to enhance business outcomes, it is not a magical solution that can manufacture instant results. Rather, organizations should treat GenAI like a sophisticated tool that can drive substantial growth to a business’s bottom line—and one that should come with clear cost benefits. A hybrid approach of introducing external models into foundation models offered by OpenAI should allow companies to scale faster while still retaining some control over model performance.
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We have yet to see how this technology will truly transform businesses, but one thing is for sure – organizations that capitalize on these innovations will set themselves apart as clear market leaders. In finance, it is reshaping customer-centric services, simplifying tax preparation and providing effective digital “assistants” that serve as financial advisors. In healthcare, GenAI can enhance personalized care and accelerate drug discovery, helping to save more lives and improve everyone’s quality of life. In the entertainment industry, GenAI can create interactive storytelling experiences that captivate audiences. For example, GenAI can empower decision making, stimulate innovation and make deep inroads into marketing, sales and R&D initiatives. It can also help organizations anticipate market shifts, adapt to changing customer preferences and optimize supply chains.
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Ninety-eight percent of the respondents in the previous chart answered the question posed in the chart above – i.e., what benefits are you seeing specifically from gen AI deployments? Thirty-nine percent cited better customers support – contact centers is a big initial use case. And you can see, the other benefits customers cite like better engagement with customers, product innovation, better data analysis, headcount savings and so on. Notably, 33% said cost savings on personnel, which is a big percentage of customers and we felt it was worth highlighting in the red. We don’t know the degree of headcount savings, but the fact that a large proportion of customers cites that benefit directly is instructive.
Understanding the upfront costs
- For example, GenAI can empower decision making, stimulate innovation and make deep inroads into marketing, sales and R&D initiatives.
- This is fresh data from nearly 1,800 information technology decision makers across industries and company sizes.
- Generative AI has been at the forefront of experimentation in many industries.
- It can also help organizations anticipate market shifts, adapt to changing customer preferences and optimize supply chains.
Along the way, though, you’ll need to understand cloud economics, which can provide a framework for AI spending, including how to grow promising AI programs and cost-effectively sunsetting AI programs that underperform. Lack of clarity on tangible return on investment for mainstream businesses, a narrow list of early winners and relentless vendor marketing around AI has caused cynicism and media backlash. But the reality remains that we have entered a new era in technology innovation that has a high probability of transforming industries, public policy, company leadership and the related fortunes of individuals and organizations. Indeed, Jyoti said there’s so much excitement around AI that companies are actually deprioritizing other initiatives to prioritize AI. “That is something that is new,” she said, not seen in her survey last year or other AI reports her team has done. This has been triggered specifically by heightened interest caused by generative AI, she said.
Be upfront with stakeholders about the challenges and limitations of measuring AI’s impact.
The most immediate and impactful application of generative AI has been streamlining internal knowledge access. Employees at every level—from compliance teams to branch staff—routinely spend valuable time searching for policy documents, procedural guidance, or answers to routine questions. A team might launch a pilot program, but because they can’t quantify the business impact, they’re unable to make a convincing case to leadership for continuing. “You need to be very thoughtful and think about your business outcomes first, and then back your project into it,” Lynch says. Yet only 49% of those using genAI are measuring the return on their investments.
For sophisticated participants, receiving advanced summaries improved their earnings prediction accuracy by 18%. In comparison, less sophisticated participants saw a 7% gain from receiving simplified summaries. For the authors, this highlighted the importance of personalization and tailoring output to align with an individual’s level of financial expertise. Cloud-based AI platforms can allow for flexible scaling as the organization’s AI needs to grow. These platforms also often offer tools, models and infrastructure to experiment and deploy AI without heavy upfront investments in hardware.
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While both groups asked a similar number of questions, sophisticated users posed targeted questions about complex financial topics or asked the chatbot to aggregate various components. In contrast, less sophisticated participants often asked broader or irrelevant questions. Measuring and maximizing AI ROI demands a clear, structured approach that addresses the unique challenges of AI implementation. Because AI spans so many use cases and functional roles, it brings new complexities to managing business expectations. More than just purchasing the latest hardware, this means integrating systems that ensure seamless data flow across all segments of the supply chain. Such integration allows for real-time monitoring and data collection, providing a comprehensive view of an AI system’s impact.
And these big-spender firms might see a smaller ROI percentage but they’ll likely see bigger NPVs. And they will set the pace for future investments — especially as and if these investments start to throw of cash and enable reinvestment. Moreover, 97% of leading gen AI adopters report that they’re achieving tangible benefits from their deployments. Adoption of gen AI is relentlessly on the rise and nearly two years in, is poised to begin throwing off enough value that it will heighten a mandate to apply AI to drive business results. As such, we believe that as we exit Q4 into 2025, the demand for AI solutions will continue to occupy the headspace of business technology pros and AI momentum will maintain its accelerated pace.