7 steps to become an AI-enabled enterprise

Challenges old companies face when adopting AI and 7 steps they can take to stay competitive.


7 steps to become an AI-enabled enterprise

While platform companies – firms like Google, Amazon, and Alibaba – continue to collect tons of data and train their systems using information on consumers’ lifestyles, most enterprise leaders seem to underestimate the effect this will have on their businesses. A general AI strategy is needed for old world companies to keep up with this competition.

Challenges for the established economy

Apart from their own inability to change effectively and the intra-industry competition, large companies also face an underestimated challenge in the form of stiff competition from platform companies in three main ways. These are:

  1. The ability to "burn" money

Platform companies have more financial resources they can leverage to invest with no urgency to prioritize budgets. In contrast, companies from the old economy have very little money to play with since they are constantly subject to pressure from the capital market, shareholders, and customers. For example, if Pfizer or Bayer were to invest USD 500 mn in cancer research – which is related to their core business – and come up with no drug, their CEO would be fired immediately. Google or Alibaba, on the other hand, could burn money on the same cancer research – a non-core project – and move on. This is coupled with the mindset companies like Amazon have to take risks and invest massively in R&D, including on untested AI technology, which is lacking in old-world companies even when they do have the cash to spare.

  1. The strategy to hijack direct customer relationships

Today, as customer engagement, advertising and sales have moved on to platforms like Facebook, Google, and Amazon, these companies can easily hijack the direct relationship between established companies and their customers. As an enterprise owner, you might get analytics and some data from platform companies, but they can then use the same data and AI to enhance product recommendations, customize shopping experiences and improve targeting to offer goods and services from a pool of brands that keep customers from switching.

  1. The power to collect massive data for building general AI

The range of products and services offered by platform companies – think Amazon’s marketplace, Kindle, Echo, and more – helps them collect endless amounts of data and thus create their own general AIs. These general AIs can then be deployed in different areas like finance, shipping, entertainment, and healthcare, further cementing the companies’ connection with a customer. This disruptive approach is not possible for enterprises from the old economy..

AI is the strongest tool to overcome the threats

While a strong brand, outstanding services, and innovation can help in survival, turning exponential is the only way to successfully compete against companies that are already exponential and trying to touch billions of customers across industries. AI is possibly the only tool today that can help ward off the competition, making use of the strong side of established companies: their experience. Their own general AIs can help established companies run processes autonomously across their organizations while retaining their knowledge and monetizing their data and experience. But, given the relatively limited breadth of data with these companies, a pooled approach would work better. Here is a step by step strategy to execute this idea:

  1. Established companies collect every piece of data within the company.

  2. Give data to a secure and independent intermediary platform operating a shared data pool for an established economy.

  3. In return, they get access to a shared pool of aggregated and semantically organized data.

  4. They use this data and the necessary technology to build their own corporate general AI.

  5. Outcome-based on corporate general AI - New business models, offerings, services, etc.

  6. Give resulting data from new business models, offerings, services, etc. to the shared data pool.

Adapting this approach can allow companies to keep their intellectual property and create value from their experience.

AI-enabled enterprise: anything that is a process can be and will be run by AI

Any process that can be automated today can be run by AI, leading to massive savings in money and manpower. This also spares resources to innovate at a faster pace. The following seven steps can help your company become an “AI-enabled enterprise”:

  1. Create a semantic map of your data - accept continuous data flow as a foundation for future strategy.

  2. Automate your IT operations - automate IT operations to receive immediate value brought by AI and to collect data; also make them autonomous.

  3. Rethink your strategy - think about a new (exponential) business model.

  4. Retrain your entire organization top-down - prepare and train your organization for an AI-enabled enterprise and for accepting a new business model.

  5. Expand autonomous operations to other business processes - use company knowledge gathered through IT automation to make more processes autonomous.

  6. Embrace predictive analytics - use data from the semantic map to expedite, improve business processes and future business events.

  7. Consider data-driven processes - use data and AI to generate outcome-based processes.

Strengthen your core, widen your horizons

All data collected in the entire company eventually ends up in the IT environment: stored in applications, databases or storage systems. Thus, it is recommended to start setting up an AI in the IT environment – the core of your enterprise. Most importantly, come out of your comfort zone – your existing business and the industry you operate in right now. It doesn’t help you to simply develop something for the media industry when you are a media company. You have to think across industries and develop something that adds an additional value for your customers and thus opens a new industry for you.


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