Businesses Demand Results as AI ROI Falls Short: Is the Hype Justified?

Despite high expectations, businesses integrating generative AI tools have struggled to achieve desired returns, raising doubts about the technology’s efficacy.

Artificial Intelligence (AI) has been touted as a game-changer for businesses across various sectors, promising increased efficiency, improved decision-making, and enhanced customer experiences. However, a recent study by IBM revealed that the average return on investment (ROI) for Gen AI projects in the past year was a mere 5.9%. This discrepancy between the theoretical promise and practical implementation of AI has led many businesses to question whether the technology is over-hyped. As the demands for results grow louder, experts predict that 2024 will be the year when businesses demand tangible ROI from AI.

The Reality of AI Implementation:

Arijit Sengupta, CEO and founder of AI app developer Aible, and creator of Harvard Business School’s course “AI in Market Facing Functions,” believes that businesses are becoming increasingly impatient for AI results. Despite the success stories of early adopters, many organizations are still struggling to achieve significant returns on their AI investments. Sengupta attributes this to a crucial gap between user expectations, driven by aggressive marketing, and the actual capabilities of AI technology.

Challenges in Achieving ROI:

One of the main challenges businesses face in achieving ROI with AI is the lengthy lead time for implementation. Sengupta argues that if the implementation process takes longer than a month, the underlying technology becomes outdated before the project is completed. He suggests that projects should ideally be completed within hours, days, or weeks at most. However, many companies are waiting too long to gather what they consider to be “good enough” data before implementation. Sengupta emphasizes that perfect data is a pipe dream and urges businesses to prioritize getting the technology into the hands of end-users quickly. By incorporating user feedback and continuously improving the AI system, businesses can achieve better results over time.

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The Gap Between Marketing and Reality:

Sengupta highlights the discrepancy between the marketing hype surrounding AI and the actual implementation process. He argues that the marketing messaging fails to communicate the configuration and context transfer required to make AI truly shine. This lack of transparency often leads to customer dissatisfaction when the technology does not live up to the lofty promises made in promotional materials. Sengupta believes that a more realistic portrayal of AI’s capabilities would help manage expectations and foster greater satisfaction among users.

The Road Ahead:

As businesses demand tangible results from their AI investments, the pressure is on for AI developers and organizations to bridge the gap between expectations and reality. Sengupta suggests that businesses should focus on quick implementation, incorporating user feedback, and continuously improving the AI system. By doing so, they can maximize the potential of AI technology and achieve the desired ROI. As the technology evolves and businesses become more adept at harnessing its power, the true value of AI may finally be realized.

Conclusion:

The discrepancy between the hype surrounding AI and its practical implementation has left many businesses questioning the technology’s efficacy. As demands for ROI grow louder, organizations are becoming increasingly impatient for results. However, challenges such as lengthy implementation lead times and unrealistic expectations hinder the achievement of significant returns on AI investments. By prioritizing quick implementation, incorporating user feedback, and managing expectations, businesses can bridge the gap between marketing hype and the reality of AI. As the technology continues to evolve, 2024 may indeed be the year when businesses finally see the true value of AI.

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