How AI is destroying the business model

Gone are the days when creating a business model at the time of company’s conception would see an organisation through decades of growth. As waves of digital disruption and transformation redefine standards of service, it’s no longer viable for a business model to exist as a document in company archives. According to a recent KPMG survey, more than 44% of CEOs said they expect their companies to change their business model in the next three years.

The proliferation of Artificial Intelligence (AI) is one of the main reasons traditional business models are becoming increasingly obsolete. However, the conversation around AI is largely focused on the disruption it is causing within a company or industry, specifically in terms of the superior technology now available to enhance existing capabilities. Few look beyond the surface to all the systems that are being disrupted, including the basic rules of the game for creating and capturing economic value. These were once fixed in place for years, even decades, as companies tried to execute the same business models better than their competitors did. But now, business models are subject to rapid displacement, disruption, and, in extreme cases, outright destruction.

What’s making traditional business models obsolete?

Unfortunately, innovation across most sectors remains piecemeal or incremental – rather than transformational, fundamental and company-wide. Hence the impact on the bigger picture often goes undetected but this doesn’t make it any less transformative. In the financial services sector for instance, innovations such as online payment systems and trade digitalisation have changed the way these firms interact with their customers. As consumers move more towards online and anytime convenience for them, a business model heavily reliant on physical interactions will quickly become obsolete. One only needs to look at the challenge posed by digital-first banks (like Goldman Sachs Marcus) to the established brands to see this.  

This changing nature of the game requires the introduction of agility into the organisation’s business models. The IT cycle is now much shorter than the average finance cycle, as the speed of innovation demands constant changes to the IT infrastructure of a company. Hence, companies can no longer plan and budget for projects only once a year – they must be able to react fast to change and fluctuations with the appropriate investments and skills.

While most AI initiatives create competitive advantage by perceiving an entirely new opportunity, enhancing current efforts, supplying a market segment that others have ignored, or creating new markets, connected devices that feed a constant stream of data about functionality, usage, production, needs and more to a central location will create even more fascinating competitive transformations.

Additionally, change projects in companies using AI often don’t follow a straight path from beginning to end and circumstances change as a project develops. Hence the planning, design, development, and testing cycles are never truly over – the outcomes of which directly impact, and sometimes conflict, the underlying business model the company may have in place.

Considerations for companies looking towards agile business models

Every industry is built around long-standing, often implicit, beliefs about how to deliver specific goods or services and to make money doing so. These governing beliefs reflect widely shared notions about customer preferences, the role of technology, regulation, cost drivers, and the basis of competition and differentiation. They are often considered inviolable—until someone comes along to violate them. The process of introducing this out-of-the-box thinking into existing frameworks can begin with something as simple as identifying an industry’s primary belief about value creation and then understanding the underlying notions that support this belief.

It is then imperative to constantly question these notions, reframe them and look at them from multiple conflicting perspectives. In doing so, companies can ensure they are continuously questioning their existing business models and updating it to reflect the changing times.

As counterintuitive as it may sound, it is also possible for businesses to ‘plan to be more agile’. Agility often requires a combination of the stable and the dynamic. While it is important to be nimble, flexible and responsive, it is also crucial to create a stable foundation that allows for dynamism. Companies can build a stable backbone by incorporating structure and scale within existing organisational processes. For example, if an organisation is looking to turn its supply chain ‘smart’ – by equipping it with machine learning and AI capabilities – it must first consider the outputs it wants to achieve carefully before undergoing these change projects. Once these business objectives are defined, firms can then put in place the structural support needed for the success of the project. This includes the procurement of the technology required, defining budgets, compliance with any regulatory requirements and making sure the individuals involved have the skills needed to make this project successful.

After this foundation is in place, organisations can then allow for the agility and flexibility needed to make the digital transformation success. This approach allows firms to explore new opportunities, enhance current efforts, supply a market segment once ignored – or even create new markets entirely.

Although the integration of new technologies remains central to tackling the disruption faced by traditional companies today, it is no longer enough to incorporate new pieces of technology into legacy systems and antiquated business models. AI is not only changing how businesses work; it is also fundamentally transforming the traditional thinking and meaning of collaboration, automation, competition, and innovation. In the age of innovation, organisations should now be thought of as living organisms – in a constant state of flux in one way or another – and business models must reflect this dynamism.