Powering Enterprises with AI

In this chapter, we’ll talk about practical steps to level up your organisation when it comes to AI applications. The strategy here is mostly adapted for large enterprises with enough capital and structure to carry out a plan. On the other hand, I also take into account that large enterprises are often slower to adapt, more decision-makers need to be convinced, and thus a plan to power your organisation with AI might be harder to implement. It’s also definitely different than if you’re running a smaller organisation or if you’re a freelancer. I will treat these cases separately in the next chapter, Boosting Startups with Artificial Intelligence.

Let’s now go back to enterprises. They are organized into departments by their core function, ranging from sales/marketing to customer service, product development, et cetera. Because each of those departments has a different goal and thus is optimized for a different function...

AI Maturity Levels

Let’s look at the potential steps you might take to apply Artificial Intelligence at your workplace and what challenges you might face along the way. Gartner, a research and advisory company, has defined maturity levels for AI adoption as follows:9

Level 1 - Awareness: Conversations about AI are happening, but not in a strategic way, and no pilot projects or experiments are taking place.

Level 2 - Active: AI is appearing in proofs of concept and possibly pilot projects. Meetings about AI focus on knowledge sharing and the beginnings of standardization.

Level 3 - Operational: At least one AI project has moved to production, and best practices, experts, and technology are accessible to the enterprise. AI has an executive sponsor and a dedicated budget.

Level 4 - Systemic: Every new digital project at least consider using AI, and new products and services have embedded AI. Employees in process and application design understand the technology. AI-powered...

Solving maturity issues

Let’s now talk about how a company can transition to the next level, no matter where it starts. Building AI maturity is crucial in staying competitive in our digital world. Enterprises are challenged and beaten by technological startups because of a lack of innovation or a too-slow adaptation to changes. In this section, I discuss each level and potential challenges associated with it.

Awareness (1)

In order to ascend to the very first level, one should organize a workshop for the whole department about AI, machine learning, data science, and their potential use in real-world scenarios.

Potential challenges:

• educating staff of new ways of doing marketing,
• overcoming fear of AI and explaining it in simple terms to everyone.

From Awareness (1) to Active (2)

To progress past the first stage, one needs to connect the company’s data to the system able to analyse data. This way, the first generic algorithms can be put...

Fostering a culture of innovation

One of the key components of being successful in implementing AI at a transformational level is building your company’s culture around innovation and AI in particular.

A culture of innovation means creating a culture where every employee feels he or she has some level of autonomy to think independently and find new ways to solve problems. If you’re the one in charge, it means you should put forward your decisions, but leave an open window for new ideas coming from your team. Trust is important.

You should encourage taking a reasonable risk and allow the uncertainty of results if you want to foster innovation. Developing new ideas is an iterative discovery process and as such needs people and ideas to flow freely. Understanding that this does not always lead to a product is also a key. Failure is an important aspect of building an innovative culture. You can’t hide failures. Instead, talk them over with your team. A truly...

How to shift an existing culture

Changing a corporate culture is a difficult task, and it should be done slowly. Don’t force it; adaptation to changes at a massive scale is always painful. It should be done in steps:

• create a vision for the future,
• describe your vision in a story and pass it to your closest employees,
• create a plan of actions you want to reward and how,
• prepare materials for your employees and the necessary retraining programs.

There’s no change without tracking how employees answer to senior management strategy. You should hear feedback and act upon it to make this shift towards innovation as smooth as possible. In the end, there are three ingredients in shifting a corporate culture towards innovation:

• rewards,
• hiring,
• retraining.

By rewarding innovative behaviors, hiring new talented people, and expanding the skills of your employees, you’ll be able to create an excellent environment for innovation...

Hiring AI Talent

Often the most challenging part of executing an AI strategy is hiring talented people. There’s a shortage of talent on the market, and the best are usually picked by Google, Facebook, Amazon and other big tech companies. Even large enterprises which are not strictly technological in nature lack talent. So in order to overcome this challenge, it’s critical to understand how to attract talent to your organisation.

Computer scientists, in particular data scientists and machine learning engineers, are looking for an intellectually stimulating environment. More often than salary, what’s important is the possibility to learn, solve creative problems and be challenged intellectually. On the other hand, the fewer meetings and administrative burden,s the better for them.

Those conditions often are hard to meet in organisations with a corporate, rigid structure. That’s why changing your culture slowly to a culture of innovation is a necessary...

Building an innovative culture in enterprises

Summing up this chapter, we have covered AI maturity levels and discussed how to progress to the next level, no matter where you start. It’s crucial to become an AI-enabled company to stay competitive in the future.

A key component to progress in AI maturity is fostering an innovation culture. We’ve discussed how it’s possible to change corporate culture. It’s a slow and steady process, but it pays off in the end. An environment where innovative ideas are rewarded and not frowned upon is perfect for attracting top talent in machine learning and data science.

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9 https://www.gartner.com/smarterwithgartner/the-cios-guide-to-artificial-intelligence/

10 https://www.mckinsey.com/featured-insights/artificial-intelligence/ai-adoption-advances-but-foundational-barriers-remain

11 https://www.mckinsey.com/featured-insights/artificial-intelligence/global-ai-survey-ai-proves...