Companies are adopting AI-powered solutions at a rapid pace. In fact, “73% of U.S. companies have already adopted AI in at least some areas of their business.” Although companies are noticing immediate differences, they struggle to measure ROI. However, setting parameters to measure the effectiveness of AI investments is feasible. As technology continues to evolve, the role of AI in business operations becomes increasingly prominent.


Copyright: – “Finding ROAI: Strategic Benchmarking For AI-Powered Business Success”


SwissCognitive_Logo_RGBIndustries across retail, fitness, healthcare and more are investing in AI for various purposes. Retailers use AI for efficient customer service with self-service portals and virtual assistants. Gyms leverage AI to handle sign-ups, automate scheduling and collect feedback. Even healthcare facilities use AI to aid in medical imaging and diagnostics, such as algorithms that analyze CT scans, MRIs and X-rays. AI proves to be a versatile tool, optimizing operations and enhancing outcomes across sectors.

Steps For Achieving Your ROAI

Yet, for each of these industries, navigating AI investments necessitates strategic planning and establishing clear benchmarks for measuring ROI, as setting the stage for success involves robust metrics for evaluating AI initiatives. The term “return on AI investment” (ROAI) may sound novel, but its significance can’t be overstated. Simply deploying AI solutions without understanding their impact on business outcomes is insufficient. To achieve meaningful ROAI, CIOs must proactively align AI investments with organizational objectives and foster a culture of innovation.

Here are some essential steps for setting benchmarks and measuring the success of AI investments:

1. Focus on value-driven solutions

Rather than falling for flashy technologies, prioritize AI solutions that directly contribute to operational efficiency and business growth. Conduct thorough app rationalization, evaluating each application in an organization’s portfolio to assess its value, redundancy, performance and alignment with business goals—exercises to identify areas where AI can streamline workflows and enhance productivity.[…]

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