April 19, 2024

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Innovation that Brightens the Future

The Impact Of AI Hyperscalers On Business Innovation

5 min read

President and General Manager at Kodak Alaris, a leading provider of information capture and intelligent document processing solutions.

In the realm of artificial intelligence (AI), the term “hyperscalers” has gained prominence. The word encapsulates the immense capabilities of the world’s largest tech companies (particularly Microsoft, Google and Amazon) in shaping AI and its role in business productivity. With their vast resources and expertise, these hyperscalers are the architects of the AI revolution, redefining how businesses will operate and thrive. They are also creating tremendous opportunities that many business leaders are only just beginning to explore.

A Growing Wave Of Demand

These titans of the cloud computing world are providing intelligent automation services that are reshaping how businesses approach productivity and efficiency. We are in the early days of this growing wave. The market for AI services reached $200 billion in 2023 and is expected to expand to around $2 trillion by 2028. According to research by Deloitte, 79% of survey respondents believe generative AI will drive significant transformation within their company in the next three years.

Microsoft has positioned itself as a leader in this transformative wave, most notably with its introduction of Copilot, which is integrated into its core office applications to provide users with AI assistance on demand. Copilot leverages the technology of OpenAI, of which Microsoft currently owns 49%. This strategy of integrating AI into everyday applications has made Copilot the most accessible pathway into AI for businesses and consumers alike.

Google’s strategy also highlights the shift towards AI integration at the enterprise level. They originally focused on embedding AI into their existing product ecosystems to enhance functionality in familiar tools like Search, Maps and YouTube. Now, they are all-in on enterprise services via Google Cloud and Vertex AI, which provides APIs for foundational AI models, enabling businesses to build custom AI tools and deploy them into their applications.

With AWS and related services, Amazon has adopted a different strategy that focuses on building a robust developer ecosystem. By providing developers with tools to build, train and deploy their own AI models, Amazon is creating fertile ground for AI innovation at the grassroots level. With tools like CodeWhisperer, available free for developers, Amazon is demonstrating its commitment to enhancing developer productivity and accelerating AI applications across many industries.

We are only at the beginning of this major new trend. AI hyperscalers are reshaping the technology landscape and providing businesses with unprecedented opportunities to enhance productivity and facilitate innovation. One of the most promising applications being enhanced by these AI hyperscalers, and one that’s still under the radar, is intelligent document processing (IDP).

IDP: A Major Facet Of AI Opportunity

Data has become the new currency of business, and IDP enables businesses to get the most out of that currency. IDP software is offering new ways to leverage the most advanced AI technology to process vast amounts of information efficiently and accurately. It’s revolutionizing how businesses onboard data and integrate it into their systems, providing a robust foundation for various applications like predictive analysis, auditing, fraud detection and more.

Successful IDP solutions can connect to the AI services offered by the hyperscalers, integrating machine learning (ML) and natural language processing (NLP) services to automate the extraction and processing of data from a wide range of document types and formats, including invoices, contracts, IDs, financial statements, handwriting, emails and practically anything else common in business today. The ability to make sense of unstructured data and convert it into critical business information with a high degree of confidence is what makes IDP so valuable today.

Sectors in which large volumes of data are processed daily, like finance, healthcare and government, are increasingly turning to IDP solutions to streamline information workflows, reduce manual errors and improve productivity across the board.

Integrating AI Into IDP

The strategic integration of AI into document processing can further provide business advantages. The ability to link an IDP platform to advanced services from an AI hyperscaler enables the solution to learn and adapt, constantly improving the accuracy and efficiency of the operation while future-proofing a key element of an organization’s technology stack.

Machine learning algorithms and pre-built document models enable these systems to learn from patterns in data, automatically improve accuracy over time and make perfection a reasonable long-term goal. They can glean unique insights, identify trends and predict outcomes based on processed data, which is particularly valuable in sectors like finance, healthcare and legal, where the interpretation of document data can inform critical decisions.

In addition, natural language processing allows for the extraction and analysis of data from unstructured sources, making it possible to handle various document types and complexities with minimal need for human involvement that further decreases over time as the system learns and improves itself.

Potential Caveats To AI-Enhanced Systems

AI is driving digital transformation at a rapid pace, but the benefits do not come without some risk. IDP systems rely on high-quality data, and some of that data may contain sensitive and confidential information that must be protected. As AI advances around generative AI models, IDP capabilities move well beyond the extraction of data from documents for delivery into business systems. With generative AI models, vast amounts of data can be analyzed. However, without proper oversight of the training data and models, undesirable outputs can occur from a lack of monitoring or misuse of information.

To mitigate these risks, organizations should adopt a strategic approach that leans on IDP experts to help test and validate AI training models and integrate human-in-the-loop (HITL) procedures to further verify data quality and protect confidential information.

Redefining Enterprise Productivity

AI hyperscalers are actively redefining business productivity and taking us into a new era where AI is not just an add-on but a fundamental part of business operations, helping drive us to higher levels of efficiency, innovation and growth.

In this new business environment, where data comes from multiple sources and in diverse forms, the ability to understand, interpret and efficiently process data from various inputs is becoming an indispensable tool. I believe businesses that explore the many opportunities to leverage these technologies while strategically navigating potential risks will better position themselves for success in the age of AI.

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