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After years of relative technological stability, generative AI has taken the world by storm—so much so that McKinsey estimates that every non-AI business it will become obsolete in the next three years.
Native AI businesses—businesses built with AI at their core—are already growing. Existing corporations that need time to implement change should take note. Generative AI has created an inflection point where AI-centric models are moving forward at lightning speed and organizations still on the fence are rapidly falling behind.
I saw a similar thing happen during the dot.com boom with Blockbuster, when the business failed to digitize in time to cater to an increasingly digitally savvy audience. The same thing happened with Blackberry and its failure to adopt the touchscreen keyboard in time, making their modern device a thing of the past. Both examples are not so much about a lack of product updates as about the failure of the leadership team to drive a deeper transformation of the business in time.
While many are just waking up, time is already running out for organizations still dealing with AI. This is the bad news. The good news is that there is still time to course-correct. Any successful technological transformation it first starts with a business process transformation. It's about your employees and how people work with each other. Employees can quickly become change agents provided they are given the right tools and space to contribute. And this is something you can easily do.
Connected: Why you should incorporate AI into your business – and how to do it the right way
What is an AI-centric organization?
I see a convergence of two forces here—native AI organizations, essentially, startups that have built AI into their infrastructure from day one, automation and data at the forefront of their modus operandi, and the transformation of speed of existing organizations in AI – central entities. To survive and thrive, more organizations will need to focus on AI, making room for AI as a central “glue” in how they operate and grow in the future.
This transformation is, of course, a tall order. Any operational change can be a painful process, let alone one that affects every aspect of the business, from sales and customer service to finance and human resources. However, I think the opportunity cost of not undergoing this massive transformation is too great to ignore. Organizations must embrace AI if they want to remain competitive and relevant in the long term. So the question is not whether to become an AI-centric organization, but how to become one.
Building an AI-centric organization
Create an open dialogue about AI:
People fear the unknown. whether change is happening, and your employees think they are the last to find out, this will create a lot of anxiety and uncertainty. A McKinsey survey, for example, found that many transformation efforts fail because the goals are not aligned with each employee's work. Even more disturbing is the finding that senior leaders are 20% are more likely to feel that these goals are aligned than the rest of the workforce, leaving a wide gulf of misunderstanding between the two.
When defining your AI strategy and goals, you want to involve your entrepreneurs from all levels of your organization in how these changes will affect individual job roles. Have them communicate these changes to affected employees. Create open forums where employees can ask questions, voice concerns, and share best practices with each other. This proactive engagement may make you nervous and will require you to keep your hand up, but it will certainly pay off in increased innovation, adoption and impact.
Include all:
In addition to telling people what change is happening (a top-down approach), you also need to think about ways in which you can involve all employees in the process (bottom-up approach). An early McKinsey study shows that when employees feel like they are actively involved in a business change, they are much more likely to stick with it.
The best way to engage your workforce is to simply ask them about use cases and tools they think can solve an existing business problem. Another way is to create promptathons, which will help people come up with new AI requirements while giving you much-needed insight into the quality of existing AI algorithms. Finally, get teams to test pilot solutions and provide feedback. For example, if your customer service team needs to learn to work together with a new chatbot, work with them to co-design it. Your employees are the best innovators and they know your business processes best.
Experiment with AI-centric business models:
Pay attention to the rapid changes in the AI space – both in technology and in evolving business models. If you have a dedicated innovation team, work with them to experiment with AI-centric solutions. If you don't have one, maybe it's time to create one as AI innovation doesn't wait.
In this context, create a scalable approach to AI use cases, a clear metrics and prioritization framework, and a map of each business function transformation. An AI-centric organization requires data (and therefore organizational knowledge) to flow freely between business units and underlying platforms. This can be a costly endeavor, but it presents a unique opportunity to review and rework your entire business infrastructure. Think of it as migrating from paper memos to email. This was a big step, but nowadays, it is hard to imagine that organizations once relied only on printed materials and only on interoffice mail.
The AI way or the highway
Working with executives in many verticals, I see many of them succumb to a lot of AI intimidation. Business leaders feel increasingly pressured to adopt AI even when they are not ready to do so. This, of course, is a wrong approach. Poor Approval of AI it can do far more harm than not adopting AI in the first place. So, as a first step, make sure you focus on your business strategy.
That said, complacency isn't the answer either. If you don't have a clear strategy how AI can elevate your business, then this should be at the top of your priority list. Consult with your employees to gather insights that you might not have gained otherwise. Then get to work because time is running out and businesses using AI are already moving across the competitive landscape.