Already well on its way to revolutionizing the modern business landscape, generative artificial intelligence (AI) is projected to reach a market value of hundreds of billions by 2030. This transformative technology is not just reshaping data ownership and creating new revenue streams across diverse sectors, it’s exposing both unprecedented opportunities and complex challenges for data monetization.

For business leaders and executives, the imperative is not only to utilize generative AI but to deeply understand its far-reaching implications for data as a strategic business asset. This article provides insights for navigating the complexities of this transformation and outlines a five-step blueprint for ensuring your organization can effectively capitalize on the potential of generative AI for innovation and revenue growth.

A revolution in the making

Generative AI is capable of generating new content from text, imagery and code, extrapolating from existing datasets. Its applications are wide-ranging, from sifting through complex deal documentation in private equity to personalizing patient education in healthcare. In fact, the impact of generative AI is just beginning to be felt in healthcare, with hospitals and med tech companies starting to explore its potential for driving medical breakthroughs and streamlining operations.

However, generative AI also brings significant challenges. Businesses that rely heavily on traditional data handling methods face critical decisions. The real issue is not whether to adopt generative AI but how to do so in a way that avoids short-sighted approaches that could potentially limit future growth. This situation calls for a comprehensive reevaluation of how data is valued and utilized.

Valuing data in the age of AI

Data is central to generative AI, driving its advancements. Yet, accurately valuing this digital gold remains a complex issue, largely due to the lack of clear regulations and lack of transparency/attribution in how the AI models are using the content. Traditional methods for understanding and valuing data often fall short within the context of generative AI, prompting a need for companies to adopt a new perspective on their data assets.

This challenge is further exacerbated by a shortage of professionals who possess a deep understanding of generative AI. To navigate this situation, businesses need to find a balance between protecting their data and adopting forward-looking strategies such as licensing and innovation. This approach will not only safeguard their interests but enable them to convert their data into valuable assets and product pipelines.

Monetization strategies

In an emerging field like proactive investing, BloombergGPT offers a blueprint for monetization. Similarly, healthcare organizations are experimenting with data as a service (DaaS) models, carefully working within the parameters of HIPAA regulations.

The key to success in these areas depends on a thorough understanding and ongoing oversight of how generative AI uses proprietary data. Companies can collaborate with their industry peers, advocate clearer regulatory guidelines or limit access to their data to ensure they receive fair compensation.

Protecting data in an evolving landscape

In the AI era, data protection involves several layers. This includes working together with industry leaders and regulators, developing legal strategies, and implementing thoughtful approaches to access of proprietary content. President Biden's executive order has established a foundation for ethical and responsible use of AI, providing guidance for future initiatives.

Manufacturers, especially within the medical device sector, face the challenge of balancing innovation that uses patient data utilization and the need to protect patient data privacy. There is significant tension between the drive for development and the imperative to maintain data, with healthcare providers increasingly vocal about their concerns regarding data rights. This delicate balance underscores the need for a comprehensive strategy that not only addresses current challenges but also anticipates future developments in AI technology.

Planning your strategy for generative AI

As generative AI evolves from novel innovation to a cornerstone of modern business, organizations must be mindful, analytical and prepared to embrace the technology strategically. To effectively navigate this new landscape, companies looking to monetize in the realm of generative AI should consider a strategic approach that encompasses five essential steps:

  1. IP usage analysis: Gain a clear understanding of how generative AI platforms currently use your intellectual property, including analyzing the volume and nature of the data being ingested.
  2. Market growth monitoring: Keep a close watch on the growth of the generative AI market, segmented by use case to guide data licensing valuation and aid in pinpointing new product development opportunities.  
  3. Revenue assessment: Evaluate the potential revenue from licensing your content for model training versus creating proprietary generative AI products from your own IP.  
  4. Product strategy development: Construct a comprehensive strategy for your products, whether for direct commercialization or licensing, including detailing product features, adding value for customers, developing technical specifications, and determining pricing, packaging and delivery methods.  
  5. Risk management and access control: For licensing initiatives, it's vital to establish robust data access controls and a risk management plan (e.g., watermarking intellectual property and employing measures to block unauthorized data crawlers).

Data as the new frontier

As generative AI evolves, its impacts promise to be far-reaching, influencing every aspect of modern businesses. Data’s value is on the rise, becoming more critical and complex, transforming from a mere asset to the key differentiator between industry leaders and followers in the coming years.

Moving forward means recognizing generative AI is a catalyst for change, a driver of new business models and a guide through the complex landscape of data monetization. Its profound influence is comparable to the most significant technological shifts in history, offering limitless opportunities to those ready to adapt. Through careful strategy, expertise and creativity, businesses can carve new paths in AI era, creating a legacy that combines profitability with forward progress.

To learn more, please watch an on-demand webinar where L.E.K.’s Alexa Allen, John Frelinghuysen, Jeff Kaloski and Sheila Shah discuss this topic in greater detail.

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