"A MIT study last year showed that 95 percent of generative AI implementations fail. They generate little to no business value. There can be various reasons for this. Think of poor integration, little focus on solving real problems, and unrealistic expectations. As far as Appian CEO Matt Calkins is concerned, this is an absurd percentage for something that is seen as the breakthrough technology of this generation."
""People thought AI could work on its own," explains Calkins. "But that's not the case. AI needs other technologies to deliver real value." Calkins, therefore, advocates "serious AI," in which the technology is used primarily for essential business functions. The approach combines three elements: AI, data, and process. According to the company, this triangle forms the basis for successful implementations."
Generative AI pilots frequently fail to deliver measurable business value, with many implementations hindered by poor integration, misaligned objectives, and unrealistic expectations. AI cannot operate effectively as a standalone capability; performance depends on high-quality, accessible data for training and reasoning. Well-defined processes provide the meaningful tasks and operational context that connect AI outputs to real work and measurable outcomes. Combining AI, clean data, and process automation creates a framework that enables concrete back-office automation results and increases the likelihood of successful enterprise AI implementations.
Read at Techzine Global
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