Who Will Own Your Company’s AI Layer? Glean’s CEO Explains
The rapid evolution of artificial intelligence (AI) in the corporate sector has spurred debates and discussions about ownership and control over AI systems. As companies increasingly integrate AI into their operations, a critical question arises: who will own the AI layer? Arvind Jain, CEO of Glean, a leading enterprise search platform, has shared his insights on this pressing issue, offering a comprehensive perspective on the future of AI in business.
The Growing Importance of AI in Business
Artificial intelligence has transformed the business landscape, offering solutions that enhance efficiency, productivity, and innovation. According to a report by McKinsey, AI adoption has the potential to add $13 trillion to global economic output by 2030, increasing global GDP by about 1.2% annually. This underscores the profound impact AI can have on businesses across various sectors.
From automating routine processes to offering advanced data analytics, AI systems are becoming indispensable tools for companies seeking a competitive edge. As AI becomes more integral to business operations, understanding who controls and manages these AI systems is crucial for strategic planning and governance.
Ownership of the AI Layer: A Complex Issue
The concept of owning an AI layer is multifaceted, involving several aspects such as data ownership, algorithm control, and intellectual property rights. Arvind Jain, with his extensive experience in enterprise technology, emphasizes that ownership is not just about who builds the AI but who controls the data and algorithms that power it.
"In the age of AI, data is the new oil," Jain states, highlighting the critical role of data in shaping AI capabilities. Companies that own vast amounts of relevant data have a significant advantage in training and refining AI models. However, owning the data alone does not equate to owning the AI layer. The algorithms and the infrastructure that processes this data are equally important.
The Role of Data in AI Ownership
Data privacy and security have become paramount concerns as businesses collect and utilize data to power AI systems. Recent statistics indicate that 79% of business leaders believe that data is a vital asset, yet only 33% have a comprehensive data strategy in place. This gap highlights the challenges companies face in managing and leveraging their data effectively.
Data ownership involves understanding who has the right to access and utilize data. In many cases, businesses may rely on third-party vendors for data processing, raising questions about data control and privacy. Jain points out that while companies may own the data, the AI models trained on this data are often developed by external entities, complicating the ownership landscape.
Algorithm Control and Intellectual Property
Beyond data, the algorithms that process this data are central to AI capabilities. These algorithms are often proprietary, developed by tech giants such as Google, Amazon, and Microsoft. Companies utilizing these platforms may have limited control over the algorithms, relying on external providers to maintain and update them.
Intellectual property (IP) rights further complicate AI ownership. While a company may own the data, the algorithms and models developed using this data may fall under the IP of the developer. This creates a complex ecosystem where true ownership of the AI layer is distributed across multiple stakeholders. This dynamic is particularly evident in the realm of content creation, as seen in YouTube's new AI playlist generator tailored for premium users.
Glean’s Approach to AI Ownership
Glean, under Jain's leadership, has adopted a unique approach to AI ownership, emphasizing collaboration and transparency. The company believes in empowering businesses by providing tools that allow them to maintain control over their AI systems while leveraging external expertise for development and optimization.
Jain explains that Glean focuses on creating an ecosystem where businesses can build and refine AI models using their data while maintaining transparency in algorithmic processes. This approach ensures that companies retain control over their AI layer, mitigating risks associated with data privacy and algorithmic bias.
Collaboration and Partnership Models
To address the complexities of AI ownership, Jain advocates for collaboration and strategic partnerships. By partnering with AI experts and technology providers, companies can leverage cutting-edge innovations while maintaining oversight and control over their AI systems.
According to Deloitte, 57% of organizations are already partnering with AI specialists to enhance their capabilities. These partnerships enable businesses to access advanced AI technologies and expertise, fostering innovation while ensuring that the company retains strategic control over its AI assets.
The Future of AI Ownership
Looking ahead, the question of AI ownership will continue to evolve as technology advances. Jain predicts that as AI becomes more sophisticated, businesses will need to develop robust strategies for managing and controlling their AI layers. This includes investing in AI talent, building in-house capabilities, and establishing clear governance frameworks.
Moreover, regulatory developments will play a crucial role in shaping AI ownership. Recent initiatives by the European Union and the United States to establish guidelines for AI ethics and governance indicate a growing recognition of the importance of regulation in ensuring responsible AI use. Companies will need to navigate these regulatory landscapes carefully to maintain compliance and ethical standards. As the focus on regulation intensifies, it is also important to address the well-being of those involved in AI, as evidenced by AI enthusiasts showing early signs of burnout.
Conclusion
The question of who owns a company’s AI layer is complex, involving considerations of data control, algorithmic transparency, and intellectual property. As AI continues to redefine business operations, companies must proactively address these issues to harness the full potential of AI while safeguarding their interests.
Arvind Jain’s insights underscore the importance of collaboration, transparency, and strategic planning in navigating the challenges of AI ownership. By adopting a holistic approach that integrates data strategy, algorithmic control, and partnership models, businesses can position themselves to succeed in the AI-driven future.
Ultimately, the ownership of the AI layer is not just about technology but about leadership, vision, and the ability to adapt to an ever-changing digital landscape. As companies chart their paths forward, they must consider who controls their AI systems and how these systems align with their broader business objectives. As industries evolve, the integration of AI is exemplified by AI startup Tem's recent funding to transform electricity markets.