MIT research identifies human factors as key obstacles in digital transformation failures
By
Esther Shein
The bagel they save for the regulars. Don't skim, savour.
Summary
MIT Sloan research identifies that digital transformations fail because companies have already addressed the easier technical challenges and now must tackle harder human and organizational issues. Key failure points include ineffective communication, faulty data strategies, and neglecting the people side of transformation. To become future-ready, organizations must focus on both operational efficiency and customer experience, recognizing that digital readiness is an evolving target requiring continuous capability development.
Key quotes
· 3 pulledThe easy things have been done and the things that are left are hard.
However, future-ready is always a moving target; companies must continuously evolve their capabilities and generate new value from digital.
Ineffective communication, faulty data strategies, and shortchanging the people portion of transformation are just a few ways digital journeys take wrong turns or fizzle out.
You might also wanna read
MIT Study: 95% of Enterprise AI Pilots Fail Due to Organizational Gaps, Not Technology Flaws
MIT research reveals that 95% of enterprise AI pilots fail to deliver measurable business impact, not because the technology is flawed, but
selector.ai·9mo ago
Persistent Software Failures: Why Organizations Don't Learn from Past Mistakes
The article examines the persistent problem of software failures despite decades of experience and increasing IT budgets. Drawing parallels
spectrum.ieee.org·6mo ago
MIT Research Shows Most AI Projects Fail to Generate Profits, Highlighting Continued Need for Human Skills
MIT research reveals that most AI implementation projects are failing to generate profits, with fewer than 1 in 10 AI pilots making real mon
interviewquery.com·9mo ago
Why enterprise knowledge systems have failed for 60 years and what AI might change
The article discusses why enterprise knowledge systems have failed for over sixty years, based on the author's experience demoing an AI syst
felixbarbalet.com·1mo ago
Research on AI Failure Modes: How Misalignment Scales with Model Intelligence and Task Complexity
This research paper examines how AI system failures scale with model intelligence and task complexity, exploring whether failures manifest a
Why AI-Driven Synthetic User Testing Fails: A Case for Real UX Research
The article argues against the growing trend of companies using AI-driven "synthetic" user testing as a replacement for real UX research wit
Smashing Magazine·1y ago