Here are 3 ways Chief AI Officers and other leaders can explore what’s possible with generative AI and leverage this strategic technology during a critical time for differentiation
Strategic technology trends, by definition, have potential to significantly impact a business, industry or society. In their early years, as they move along the technology adoption lifecycle, these trends provide significant potential for differentiation before eventually becoming table stakes.
This is undoubtedly true for generative AI, which at this point, is more than a trend. It’s here to stay after recently passing the peak of previously inflated expectations. Yet even in these early years, differentiation through generative AI use is not guaranteed. Chief AI Officers and their counterparts such as CTOs, CIOs, CDOs, strategists and product managers need to explore what’s possible with generative AI technology, and seek both obvious and non-obvious opportunities.
For example, consider FeatherSnap, a solar-powered, smart birdfeeder with AI recognition. This is a wonderful example of how generative AI can be deployed as a seamless and integrated part of a product. (Spoiler alert: this birdfeeder has identification capabilities for over 2,000 species encompassing the 7.2 billion birds native to North America). FeatherSnap is delighting customers with these capabilities for sure, but behind the scenes, they’re also solving an immense data and analytics challenge for their business. If a birdfeeder can differentiate from their competitors using generative AI, you can, too.
Here are three ways leaders can explore what’s possible with generative AI and begin to think about leveraging this technology for differentiation:
- Disrupt Porter’s Five Forces
In one of his landmark books, titled Competitive Strategy, Michael E. Porter describes the five forces of industry competition as 1/ the entry of new competitors, 2/ the threat of substitutes, 3/ the bargaining power of buyers, 4/ the bargaining power of suppliers, and 5/ the rivalry among existing competitors. The Five Forces Model has long been used by business strategists to think about the rules of competition and the respective headwinds and tailwinds produced as a company operates within the context of its external environment.
While digital business models clearly disrupt the five forces, generative AI takes this one step further. With hundreds of open-source AI algorithms available for technology providers, and low switching costs for buyers, the entry of new competitors and the threat of substitutes is ubiquitous. The bargaining power of buyers is also amplified through freemium products and the wealth of information, discussion and training materials available. The ease of API use breaks down the bargaining power of suppliers by streamlining the ability to form new business partnerships and manage existing ones. All this is great news for new entrants, as well as incumbents, who look to enter the market with new AI-enabled capabilities.
- Tap into unstructured data and multi-modal AI
When compared to structured data, enterprise organizations have long-struggled with unstructured data. MIT estimates only 18% of organizations are able to fully take advantage of it. Generative AI is clearly a powerful way to access and make sense of data, and deploy data insights for business benefit.
With this new goldmine of information related to unstructured data across the enterprise, business leaders should think about how data can be leveraged both internally and externally. In addition, as we see examples of multi-modal AI, such as image and text captioning, video understanding, and product recommendations, business leaders should think about how multi-modal can enable and drive more accurate, relevant, and comprehensive use cases and results for their organizations.
- Focus on outcomes
The most recent way generative AI is expanding what’s possible for businesses is via agentic AI—the ability for AI to be directed towards achieving specific, and sometimes long-running, goals or objectives instead of just discrete tasks. For example, AI agents are already being used to work alongside human employees, automating tasks and streamlining workflows.
Since agentic AI has the capability for customization, autonomy, integration, task automation, and human-agent collaboration, perhaps the best way to envision what’s possible is to think of AI becoming not just an assistant for granular tasks, but a human-like companion and collaborative partner that can think for itself and execute a multitude of complex tasks to achieve a specific goal or objective. The point here is for business leaders to think big; think about holistic business outcomes and holistic processes for AI to solve, not just tasks.
Final Thoughts
By thinking about the Porter Five Forces Model, how to leverage unstructured data, and focusing on outcomes, CAIOs and other leaders can continue to explore what’s possible for generative AI and their business, and move from today’s quick wins to tomorrow’s big bets.
For more inspiration on this topic, don’t miss FeatherSnap’s story in the BBC: “The Art of Possible: Generative AI.”
Thank you to Amazon Web Services (AWS) for sponsoring this week’s newsletter.
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