There’s little doubt that Artificial Intelligence (AI) is driving the decisive strategic elements in multiple industries, and algorithms are sitting at the core of every business model and in the enterprise DNA. Conventional wisdom, based on no small amount of research, holds that the rise of AI will usher radical, disruptive changes in the incumbent industries and sectors in the next five to 10 years.
Additionally, it’s never been a better time to launch an AI venture. Investments in AI-focused ventures have grown 1800% in just six years. The rationale behind these numbers comes, in part, from the fact that enterprises expect AI to enable them to move into new business segments, or to maintain a competitive edge in their industry.
Strategists believe this won’t come as a surprise to CXOs and decision-makers as acceleration of AI adoption and proliferation of smart, intuitive and ML algorithms spawn the creation of new industries and business segments and overall, trigger new opportunities for business monetization. However, a few questions loom large for CXOs: How will these new industries and business segments be created with AI? And, what strategic shifts can leadership make to monetize these new business opportunities?
The creation of new industries and business segments depends on dramatic advances in AI that can take a swift adoption journey to move from discovery to commercial application to a new industry. New industry segments around AI are in the making and are far from tapped. A cursory look at new age businesses: Micro-segmented, hyper-personalized online shopping platforms, GPS driven ride-sharing companies, recommendation-driven streaming channels, adaptive learning based EdTech companies, conversational AI-driven new and work scheduling are just a few of the imminent and visible examples. Yet a lot more can be done in this space.
AI adoption brings intentional efforts to adapt to this onslaught of algorithms and how it’s affecting customer and employee behavior. As algorithms become a permanent fixture in everyday life, organizations are forced to update legacy technology strategies and supporting methodologies to better reflect how the real world is evolving. And the need to do so is becoming increasingly obligatory.
On the other side, traditional and incumbent enterprises are reverse engineering investments, processes, and systems to better align with how markets are changing. Because it’s focusing on customer behavior, AI is actually in its own way, making businesses more human. As such, Artificial Intelligence is not specifically about technology, it’s empowered by it. Without an end in mind, self-learning algorithms continually seek out how to use technology in ways that improve customer experiences and relationships. It also represents an effort that introduces new models for business and, equally, creates a way of staying in business as customers become increasingly aware and selective.
Today, AI expertise is focused more on developing commercial applications that optimize efficiencies in existing industries and is focused less on developing patented algorithms that could lead to new industries. These efficiencies are accelerating the sectoral consolidation and convergence, and are less about new industry creation.
However, AI’s most potent, long-term economic use may just be to augment the discovery and pursuit of solving large, complex and unresolved problems that could be the foundations of new industry segments. Enterprises have started realizing the significance of having a long-term strategic interest and investments in using AI in this way. Yet few of the above mentioned examples are testimony to AI triggering new industry segments and business opportunities. The real winners in the algorithm-driven economy will be business leaders that align their strategies to augment AI expertise from ground zero, keep a continuous tab on blockbuster algorithms, and redefine new business segments that enable monetization of new opportunities.
AI has immense potential to jumpstart the creation of new industries and the disruption of existing ones. The curation of this as a strategic roadmap for business leaders is far from easy, but it carries great rewards for businesses. It takes a village to bring about change, and it also takes the spark and perseverance of an AI strategist to spot important trends and create a sense of urgency around new possibilities.
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