How To Stay Ahead Of The Curve

Arvin Patel is the Chief Licensing Officer – New Segments at Nokia.

Last year’s launch of ChatGPT pushed users into the world of AI at a dramatic rate that outpaced every other major software app. ChatGPT reached 1 million users within five days of its launch and 100 million users within two months. As a point of comparison, Instagram, Spotify, Facebook, Twitter and Netflix all experienced exponential growth in users, but it took each one two to 10 years to eventually reach 100 million users. ChatGPT, on the other hand, saw a “vertical” adoption rate, underscoring that AI—namely generative AI—is taking the world by storm.

But despite ChatGPT’s meteoric rise, it’s important to note that AI is not exactly a new phenomenon. Alan Turing, the English mathematician who famously cracked the German Enigma machine during WWII, was one of the first people to articulate a world with “human-like machines.” In 1950, he wrote a seminal paper called “Computing Machinery and Intelligence,” where he outlined the “Imitation Game,” now widely known as the Turing Test. This test was meant to evaluate whether a machine’s ability to exhibit intelligence behavior is indistinguishable from that of a human. Following Turing’s paper, the term “artificial intelligence” was coined in 1956 at an academic conference at Dartmouth College, and a formal area of study around the topic was created. It was a multidisciplinary field sitting at the intersection of computer science, electrical engineering and mathematics—and, to a lesser extent, psychology and philosophy.

Since its creation in the 1950s, there have been multiple waves of interest in AI, followed by stretches of “AI winters” where little investment flowed to the topic. Flash-forward to today, when investor capital is rushing to fuel companies innovating in AI, and we’re seeing another wave rising—this time propelled by “generative” AI.

So, how should business leaders ride this wave? Surely, the answer won’t be the same for everyone. We’re each faced with our own business challenges. But I believe one place to start is to better understand the underlying AI technology stack and AI’s immense set of capabilities, then make strategic investments in areas that make the most sense for your business needs.

Solutions And Services

In the past several years, tech companies have identified 10 distinct layers (nine if services and solutions are combined), spanning hardware, interface, platform, training and application buckets. Each of these layers are at different stages of development, and they each have their own technology “chokepoints” and available white space for innovation. As a leader of a large patent licensing business, I often try to see the world through a patent lens. Within the hardware and application buckets, the layers have high patentability, meaning the intellectual property is much more feasible to obtain due to the strong technical and narrower use cases of the inventions. The layers in the other buckets have lower patentability due to the lack of specificity and technicality within them—and some, like “algorithms,” are not eligible patent matter to begin with.

The World Intellectual Property Organization (WIPO)’s 2022 report estimates that AI patent filings grew 718% faster than total patent filing growth from 2016 to 2020, outpacing autonomous systems, IoT and cloud computing. Unsurprisingly, Big Tech dominates the AI patenting space—IBM, Microsoft, Alphabet, Samsung and Intel make up the top five U.S. and European AI patent holders. But as we look to the future, there are plenty of opportunities for business leaders to innovate within the two application layers: solutions and services.

• Solutions

Innovation within the solutions layer for businesses typically involves identifying and developing AI capabilities that can be used to tackle internal problems. For business leaders, one best practice involves strategically using the data your company owns to build AI-driven solutions that can make the business run more efficiently or increase revenue. For example, companies can develop and implement AI tools to handle nearly all their customer service operations. Companies can also create AI solutions that help analyze customer data like purchase histories, allowing the company to provide unique recommendations and improved marketing campaigns.

• Services

For consumer-facing AI services, companies should consider tapping into application programming interfaces (APIs). APIs essentially allow two different software programs to interact with one another. For example, a company could use the Google Maps API to incorporate geographical data into their own AI application. Alternatively, the company could develop its own API to allow other developers to build AI applications using the company’s data.

For some businesses, however, innovating in AI won’t make sense because it falls outside of the capability set of their organization. Instead, these companies can focus on keeping their pulse on new AI-driven technologies that they can purchase and implement from other places.

Increasing Adoption

According to McKinsey, “the proportion of companies adopting AI in 2022 has more than doubled since 2017,” with those that have adopted AI reporting meaningful cost decreases and revenue increases. McKinsey also notes that 50% of organizations surveyed reported having adopted AI in at least one business unit or function. The average number of AI capabilities that organizations use doubled from 1.9 in 2018 to 3.8 in 2022, with operations optimization, AI product development and customer service analytics as the top three use cases.

Based on the evidence, I believe business leaders across the board should consider investing in AI infrastructure and talent, in building capabilities for effective AI model training, and in data utilization. This may look like devising a bespoke AI strategy, exploring opportunities in consumer-facing applications, and/or patenting innovations in areas along the technology stack that make the most sense for you.

In today’s age of AI, a comprehensive understanding of AI and its branches is becoming necessary to stay ahead of the curve. Business leaders who embrace AI as a transformative technology, stay updated on its advancements and tailor this knowledge to their specific business needs can better position their businesses to win.

Forbes Business Council is the foremost growth and networking organization for business owners and leaders. Do I qualify?