Feed Drop: Why Only 10% of Companies Succeed With AI With Sam Ransbotham, Professor at Boston College
Jul 30, 2024
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In this intriguing discussion, Sam Ransbotham, a Boston College professor specializing in AI implementations, dives into why only 10% of companies succeed with AI. He highlights the common pitfalls of treating AI as a mere add-on rather than a transformative tool. Sam critiques outdated practices in healthcare, such as reliance on fax machines, and urges for innovation in tech solutions. He explores AI's evolving role in education, signaling both its potential and its challenges, while emphasizing the necessity for thoughtful regulations in this fast-paced landscape.
Companies often fail to leverage AI effectively because they apply it to outdated processes instead of innovating their operational frameworks.
Success in AI implementation relies on strong technology foundations, skilled personnel, and a willingness to rethink existing business structures.
Deep dives
Understanding AI Success Rates
Only 10% of companies are achieving significant financial benefits from artificial intelligence, but this doesn't necessarily indicate failure. Many organizations are deriving some value from AI, even if it's less than anticipated. The discussion highlights that the perception of failure may stem from unrealistic expectations about AI's transformative potential. Contextualizing success in AI involves recognizing that there are varying degrees of benefits beyond a binary fail/success dichotomy.
Key Factors for Achieving AI Benefits
Companies that succeed with AI tend to possess strong foundations in technology, talent, and strategy. Having up-to-date infrastructure is crucial; outdated tools can hinder effective AI implementation. Furthermore, the presence of skilled personnel who understand both technology and the organization's needs significantly improves the chances of success. A mere adoption of AI technologies without rethinking processes and structures often results in suboptimal benefits.
Rethinking Traditional Processes
Simply applying AI to existing outdated processes does not guarantee success; companies must innovate their operational frameworks. An example from healthcare illustrates that while optical recognition of faxed documents may utilize AI, it would be more effective to eliminate the use of faxes entirely. There's an emphasis on revisiting processes to utilize technology in transformative ways rather than sticking to old practices. Innovation in process design is essential for organizations aiming for substantial advantages through AI.
Navigating Job Change Dynamics
The deployment of AI technologies will likely lead to significant shifts in job landscapes rather than outright job loss. While some roles may be replaced by machines, the more pressing concern is employees losing their jobs to co-workers who effectively utilize AI tools. Organizations that embrace generative AI technologies stand to gain a competitive edge in cost structure, potentially leading to job losses in companies that resist change. This dynamic necessitates a proactive approach in skill development and job adaptation to leverage AI benefits.
In the time before Me, Myself, and AI returns for Season 10, we're pleased to bring you a special episode from our friends at the Modern CTO podcast. Read the episode transcript here.
From Modern CTO:
Today we’re talking to Sam Ransbotham, professor at Boston College. Sam shares with us the reason that the vast majority of companies are falling behind the AI curve, why most people just slap AI onto a problem instead of fixing it, and the ways in which technology can improve not only our business processes but also our quality of life.
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