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Writing with generative AI

Is every business thought leader writing about generative AI? (Or with it?)

Hardly a day goes by that a thought-leader consultant isn’t sharing with business executives new research or perspective about generative AI, clearly the hottest topic in technology in 2023.

Several recent articles by McKinsey – credited to human authors, not to generative AI software, we should note! – caught our eye.  In a piece entitled “What every CEO should know about generative AI”, McKinsey states:

With proper guardrails in place, generative AI can not only unlock novel use cases for businesses but also speed up, scale, or otherwise improve existing ones…[While] generative AI may eventually be used to automate some tasks, much of its value could derive from how software vendors embed the technology into everyday tools (for example, email or word-processing software) used by knowledge workers. Such upgraded tools could substantially increase productivity.

An existing use case that fits into this general category is market and competitive intelligence.  For example, Northern Light has embedded generative AI-based capabilities into our SinglePoint™ market and competitive intelligence research platform deployed at numerous large organizations worldwide. (Our application of generative AI provides answers to a researcher’s direct questions, derived from authoritative content, both internal and external, contained in a company’s market and competitive intelligence knowledge base.)

In fact, SinglePoint’s application of generative AI for market and competitive intelligence is a variation on a sample business use case that McKinsey highlights: “Helping relationship managers keep up with the pace of public information and data.” McKinsey explains that organizations implementing generative AI for this use case on their own will incur up-front costs to “develop the user interface, integrate the solution, and build post-processing layers.” Because Northern Light already has done all this work in SinglePoint, it saves a user organization the considerable “tech talent” expenses and overhead that McKinsey enumerates:

Software development, product management, and database integration capabilities are needed, which require at least 1 data scientist, machine learning engineer, data engineer, designer, and front-end developer.

That’s a lot of resources, which most corporate IT departments most likely are not prepared to dedicate to enhancing a market and competitive intelligence portal (hence the appeal of a commercial SaaS solution like SinglePoint).

McKinsey believes generative AI applications that leverage specialized content will have a large and immediate impact on business operations. As they write in another recent article, “Companies that use specialized or proprietary data to fine-tune [generative AI] applications can achieve a significant competitive advantage over those that don’t… Those who can harness niche—or, even better, proprietary—data in fine-tuning foundation models for their applications can expect to achieve the greatest differentiation and competitive advantage.”

Words to the wise… and surely not the last we’ll be hearing from business strategy consultants on this topic!

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