How to Gauge the ROI for Your AI Projects for Exemplary Success?

Where world powers across the globe are investing billions of dollars in Artificial Intelligence (AI), do the organizations scaling the technology in such regions receiving worthy ROIs (Return on Investment)? The question has been pottering around the industry for a while now. Yet the satisfactory answers remained unsolved for some. One of the major factors can be – some businesses don't have a clear understanding of what to expect from AI's ROI and believe like any other technological solution, theoretically, there will be immediate response. As for better marketing agendas, many AI vendors tend to overstate what their AI software can generate which deviates business leaders from the path of attaining the desired ROI from the technology.

While few AI applications can be easy to scale making instant returns calculations, others are far more complex and unpredictable in terms of ROI. According to a TechRepublic study, companies that successfully recognize the value of AI and ML technologies usually fail to gauge how its investment can be beneficial for them. The revelations of the study say while around 56 percent of respondents foresee that implementing AI/ML solutions would be more complicated than previous IT projects, 53 percent are quite unsure if the solutions' users have a clear understanding of enterprise AI/ML projects. Therefore, unless businesses and solution users don't have a clear understanding of AI's ROI, they are more prone to risking their big-budget AI investments.

To enlighten businesses on how they can better plan their AI ROI in simple steps, BCG, the American management consulting company, noted, the experience of AI pioneers that suggests six moves to separate the winners from the rest. These steps include:

Integrate AI into Business Strategy: What are your business objectives and how can AI help you meet them? Zero in on the initiatives with the highest potential impact.

Prioritize revenue growth over cost reduction: AI can cut costs and quick wins can spark enthusiasm. But the greatest value will be from revenue and growth, embedding AI more deeply into business.

Take a bigger risk to achieve greater impact: More companies that invest in large, high-risk initiatives see value than those focused on low-risk projects – 50% Vs 23%. But such risks should be part of a calculated business strategy.

Align AI development with its usage: AI should be designed collaboratively with business and process owners. It's 10 percent about algorithms, 20 percent about technology and 70 percent about the business application.

Treat AI as a business transformation: AI initiatives shouldn't exist in isolation. Among companies generating value from AI, 88 percent tightly link their efforts to company-wide digital transformation.

Invest in AI talent, governance, and process change: Investing in recruiting, reskilling and training increases the odds of seeing results from AI – as does embracing agile and robust data platforms and governance.

Moreover, grabbing help from outside consultants, and AI vendors who possess the expertise in specific company verticals and business areas can also be beneficial. Companies can also avail the perks of use cases pre-packaged by AI vendors in context to specific industry verticals.