Digital Transformation is the process of taking rote or manual processes within a business and digitizing them. This is done to improve efficiency, to collect better data on processes, and to optimize the process through analytics.
Take the accounting arm of a firm. Prior to digitization, it used to manually enter ledger entries for the business. This required an army of accountants doing a lot of manual transcription. That transcription was at risk of error (scribbled a 1 instead of a 7) and was costly in terms of man hours.
The first digital transformation was taking the physical ledger books and using a computer with accounting software for that data entry. This made access of that information quicker and more ubiquitous, even if it was being manually entered by people (via a keyboard instead of pen and paper). Now imagine having automated data entry, wherein the actual business transaction was digitally recorded and thus went directly to the accounting back end.
Finally, imagine the categorization of those ledger entries being governed by rules that make categorization and the flow of information into their respective accounting identities far more seamless. The ability to identify outliers, suspicious values, or patterns within the data becomes far quicker, more attainable, and thus more actionable from a business standpoint.
What will AI do for Digital Transformation?
What we described above was a process that began with the advent of computers in the office (say 1970s-1980s), and continues to this day. What's in store for tomorrow? First, the prevailing trend will continue, just across more "physical domain" work. Think of various industries such as materials, industrials, construction, or energy. The digitization of various parts of these businesses through more connected devices (e.g., capturing telemetry and data on-site) will deepen the penetration of digital transformation across all aspects of business ("from spreadsheets to atoms").
But for businesses that are already well underway with digital transformation, AI presents an intriguing solution to a growing problem: how to efficiently draw insight from an ever-increasing set of disparate data. As McKinsey notes, "Building value with gen AI requires the same strong competencies needed for a successful digital transformation, including a clear strategy, an in-house digital-talent pool, and a responsive and scalable operating model."
Take the application of AI in financial services, a core focus of ModuleQ. There are various manual processes requiring the retrieval, collection, and analysis of data. As AI tools better understand the personal workflows of bankers and financial advisers, information retrieval can be accelerated through the application of AI.
This is an exciting frontier for firms that are well underway with digital transformation but may be reaching the limits of efficiency, due to common problems such as siloed information, regulatory overhang, process overload, or the need for workers to constantly context switch.
By enabling workers to continue riding the digital transformation wave without the associated headwinds, AI is poised to deliver another generation of productivity gains for workers. Delivering these AI solutions to the financial services sector is ModuleQ's focus.
Accenture: Digital transformation is the process by which companies embed technologies across their businesses to drive fundamental change. The benefits? Increased efficiency, greater business agility and, ultimately, the unlocking of new value for employees, customers and shareholders.
McKinsey: Digital transformation is the rewiring of an organization, with the goal of creating value by continuously deploying tech at scale.
Salesforce: Digital transformation is the process of using digital technologies to create new — or modify existing — business processes, culture, and customer experiences to meet changing business and market requirements. This reimagining of business in the digital age is digital transformation.
Read ModuleQ's white paper on AI Use Cases in Investment Banking.