IBM Institute for Business Value: Rethinking your approach to AI
“Organizations need to stay grounded in what practical things AI can help them achieve”
IBM knows a thing or two about artificial intelligence (AI); its Watson system is a perennial AI market (and market share) leader, despite stumbles in the healthcare industry.
So when IBM speaks about AI, people listen. Recent guidance from the IBM Institute for Business Value* to enterprises exploring AI boils down to this: “To succeed, resist the urge to indulge in what fantastical things AI can do and stay grounded in what practical things AI can help you achieve.”
The authors of IBM’s paper state, “Successful AI deployments are born of explicit business challenges and tied to real business results… Organizations need to be strategic about AI – but don’t necessarily need an ‘AI strategy’.” They elaborate on this last statement: “Although the intention [of an AI strategy] is to elevate the importance of AI, and to embolden it with focused attention and resources, the reality is quite different: You may advance AI, but may fail to advance the organization. And what doesn’t eventually advance the organization ultimately ends up costing it.”
In other words, an organization’s focus should be on using AI to solve practical problems. IBM says the first step in identifying such a problem is to “consider how much ‘data wealth’ is available—whether there’s sufficient economically valuable data that can be acted upon by a potential AI-based solution.”
Market and competitive intelligence clearly falls into this category. Many large enterprises license millions of dollars of third-party content, such as subscription market research and analysis reports, annually to inform their strategic planning, product development and marketing activities. They also invest similar amounts in internally-generated market research and customer insights studies. So the “data wealth” is significant.
What useful AI application could work against this data? A knowledge management system with machine learning-based capabilities, optimized for market and competitive intelligence. And best of all, it doesn’t have to be developed by a savvy enterprise; it already exists as a commercial SaaS-based offering: SinglePoint™ from Northern Light. In SinglePoint, machine learning enables:
- Computer-generated insight summaries based on an automated analysis of the important ideas in a document;
- Automatic refinement of a user’s search query; and
- Automated generation of a “Recommended Reading List” specific to the interests of each user, analogous to what shoppers on Amazon see when the system suggests other products they may be interested in, based on their past purchases.
In its paper, IBM also talk about the importance of focusing on how AI “will actually deliver value with the humans who interact with AI.” And that is the very essence of an AI-enriched knowledge management system for market and competitive intelligence: It is a tool that enables business professionals throughout an enterprise to make better business decisions, more fully informed by the research assets of the organization. It does not replace the human, it augments them.
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* IBM Institute for Business Value is one of dozens of authoritative sources contained in Northern Light’s Thought Leaders Content Collection, available to SinglePoint subscribers directly from Northern Light, and to individuals and companies through Amazon’s AWS Marketplace and the Amazon Data Exchange.