Artificial intelligence (AI) isn’t a nebulous concept that will define a distant future. AI is here, it’s now, and it’s changing how companies, society and our economies operate.
Data- and AI-driven organizations compete differently. They exhibit a new kind of operating architecture that redefines how they create, capture, share and deliver value to their customers. Companies that operate under the traditional model need to reinvent themselves around the AI model, eliminating silos and rethinking their business and operating models to improve scale, scope and learning.
These organizations also have data utilities at the core of their enterprises — called AI factories in the Harvard Business Review report, “Competing in the Age of AI.” Data utilities ingest a wide variety of data: primary, secondary, tertiary, proprietary, external, alternative, etc., to power algorithms, which can be developed to come up with new predictions, creating an infrastructure that can then deliver new types of services to customers.
A key shift in the AI operating model is that the AI algorithms are central not peripheral. AI is not an add-on to data; data is managed to power AI.
AI’s universality and impact
AI is no longer the preserve of specialized tech companies or technicians. All firms, no matter what industry they operate in, can leverage AI in every part of their business. All companies need an AI factory, all companies need to think of themselves as being part of an ecosystem or driving an ecosystem, and leaders and staff at all levels need a working understanding of machine learning, AI, networks and ecosystems and how they can be applied. This presents tremendous opportunities for companies across all industry sectors, from AI-driven cybersecurity to IT automation to marketing and personalization.
As AI alters the operating model of organizations, it is also driving fundamental changes to our economy and society not seen since the Industrial Revolution. The world that emerges over the next decade will be very different to what we know today, and organizations need to be ready by embracing AI into the very fabric of their business.
How does a traditional company become an AI-first organization?
Most importantly, act now! Don’t wait for your competitors, and don’t wait until you can do everything at once. Find a catalyst. Define opportunities where automation can remove friction from human processes such as prediction or decision-making. Then build on those successes. The transformation journey is a long one, so establish a long-term objective and start building towards it. As you do so, your business will get better.
Don’t be afraid of the technology. There is no magic machine learning, and you don’t need a PhD to understand the concepts. Learn, educate yourself and your employees through the many online resources available and, if you need to, hire technical talent or crowdsource the solution. When hiring outside expertise, be sure to ask the right questions by focusing on your business needs, rather than on the technology.
Make ethics the cornerstone of your solutions and your organization. Inherent bias programmed into algorithms, breaches in cybersecurity and consumer data theft can cause great harm, so it is crucial that ethics, business criteria and technology decisions are all aligned. Think through your approach to consumer privacy and the use of personal data — and the regulations that govern it (e.g., General Data Protection Regulations). There are solutions available to help you do this, but you have to design ethics into your solutions from the beginning. It’s difficult to retrofit for ethics, security, or privacy.
Think beyond your pilot or proof of concept. The insights from your AI must integrate back into your organization. The technology is the easy part; if the organizational structures remain the same, your transformation efforts are likely to stall. Expect internal resistance, but know getting this done will be your company’s core strength and a competitive differentiator.
As you transform your organization, you will realize greater opportunities to drive business model innovation — opportunities to leverage the network effect of AI, and to rethink your strategic options for the services you provide to your customers. Think creatively, outside of your industry vertical and innovate to provide greater value for your customers.