The jury is still out on whether AI adoption is really boosting the bottom line and driving business value. It is visible to all โ ๐ต๐ฑ% ๐ผ๐ณ ๐ด๐ฒ๐ป๐ฒ๐ฟ๐ฎ๐๐ถ๐๐ฒ ๐๐ ๐ฝ๐ฟ๐ผ๐ท๐ฒ๐ฐ๐๐ ๐ฎ๐ฟ๐ฒ ๐ณ๐ฎ๐ถ๐น๐ถ๐ป๐ด, according to an MIT study.
Why? In my view, the rush for shiny demos, shallow objectives, and the lack of clear mapping between business goals and AI use is fueling this misalignment.
Large language models (LLMs) seem simple. You prompt and get results. However, in reality, implementing them in production and integrating within business flows requires both experience and expertise. Starting a generative AI project is easy. Yet, customizing it to business objectives and delivering consistent, predictable outcomes is where things become difficult.
Those who manage to cross these barriers, however, end up with solutions that deliver real and measurable value.
๐ฅ๐ฒ๐ฝ๐ผ๐ฟ๐ ๐ฐ๐ผ๐ฝ๐ ๐ฎ๐๐ฎ๐ถ๐น๐ฎ๐ฏ๐น๐ฒ ๐ต๐ฒ๐ฟ๐ฒ – https://mlq.ai/media/quarterly_decks/v0.1_State_of_AI_in_Business_2025_Report.pdf
๐ ๐๐๐๐ฎ๐ฐ๐ต๐ฒ๐ฑ ๐๐ฐ๐ฟ๐ฒ๐ฒ๐ป๐๐ต๐ผ๐ ๐ป๐ผ๐๐ฒ: ๐๐ถ๐ฎ๐ฎ๐ข๐ณ๐ช๐ป๐ข๐ต๐ช๐ฐ๐ฏ ๐ช๐ด ๐ฐ๐ฏ๐ฆ ๐ฐ๐ง ๐ต๐ฉ๐ฆ ๐ฎ๐ฐ๐ด๐ต ๐ฃ๐ข๐ด๐ช๐ค ๐ถ๐ด๐ฆ ๐ค๐ข๐ด๐ฆ๐ด ๐ง๐ฐ๐ณ ๐จ๐ฆ๐ฏ๐ฆ๐ณ๐ข๐ต๐ช๐ท๐ฆ ๐๐. ๐ ๐ฆ๐ต ๐ช๐ฏ ๐ต๐ฉ๐ช๐ด ๐ด๐ค๐ณ๐ฆ๐ฆ๐ฏ๐ด๐ฉ๐ฐ๐ต, ๐ข๐ง๐ต๐ฆ๐ณ ๐ง๐ข๐ช๐ญ๐ช๐ฏ๐จ ๐ต๐ฐ ๐ฑ๐ณ๐ฐ๐ท๐ช๐ฅ๐ฆ ๐ข ๐ถ๐ด๐ฆ๐ง๐ถ๐ญ ๐ณ๐ฆ๐ด๐ฑ๐ฐ๐ฏ๐ด๐ฆ, ๐ต๐ฉ๐ฆ ๐ด๐บ๐ด๐ต๐ฆ๐ฎ ๐ฃ๐ฆ๐ง๐ฐ๐ณ๐ฆ ๐ฃ๐ฆ๐ช๐ฏ๐จ ๐ณ๐ฆ๐ฅ๐ช๐ณ๐ฆ๐ค๐ต๐ฆ๐ฅ ๐ต๐ฐ ๐ข ๐ฉ๐ถ๐ฎ๐ข๐ฏ ๐ข๐จ๐ฆ๐ฏ๐ต,ย ๐ณ๐ฆ๐ฅ๐ถ๐ฏ๐ฅ๐ข๐ฏ๐ต๐ญ๐บ ๐ข๐ด๐ฌ๐ด ๐ง๐ฐ๐ณ ๐ข ๐ฅ๐ฆ๐ด๐ค๐ณ๐ช๐ฑ๐ต๐ช๐ฐ๐ฏ ๐ฐ๐ง ๐ต๐ฉ๐ฆ ๐ช๐ด๐ด๐ถ๐ฆ ๐ข๐จ๐ข๐ช๐ฏ! ๐๐ฉ๐ช๐ด ๐ค๐ณ๐ฆ๐ข๐ต๐ฆ๐ด ๐ง๐ณ๐ถ๐ด๐ต๐ณ๐ข๐ต๐ช๐ฐ๐ฏ ๐ช๐ฏ๐ด๐ต๐ฆ๐ข๐ฅ ๐ฐ๐ง ๐ด๐ถ๐ฑ๐ฑ๐ฐ๐ณ๐ต. ๐๐ฆ๐ค๐ฉ๐ฏ๐ฐ๐ญ๐ฐ๐จ๐บ ๐ด๐ฉ๐ฐ๐ถ๐ญ๐ฅ ๐ฃ๐ฆ ๐ฅ๐ฆ๐ด๐ช๐จ๐ฏ๐ฆ๐ฅ ๐ต๐ฐ ๐ง๐ฆ๐ฆ๐ญ ๐ฎ๐ฐ๐ณ๐ฆ ๐ฑ๐ฆ๐ฐ๐ฑ๐ญ๐ฆ ๐ค๐ฆ๐ฏ๐ต๐ณ๐ช๐ค, ๐ณ๐ฆ๐ฅ๐ถ๐ค๐ช๐ฏ๐จ ๐ง๐ณ๐ช๐ค๐ต๐ช๐ฐ๐ฏ ๐ณ๐ข๐ต๐ฉ๐ฆ๐ณ ๐ต๐ฉ๐ข๐ฏ ๐ข๐ฅ๐ฅ๐ช๐ฏ๐จ ๐ต๐ฐ ๐ช๐ต.
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I am buildingย Beaconcross Technologiesย โ we help companies with Conversational & Agentic AI/ML projects
Author โ William Lewis