7 Steps to Infuse AI in Your Business

Infusing and Scaling AI Remains a Challenge

“The latest McKinsey Global Survey released in November 2019 found that artificial intelligence is having a positive impact on business outcomes, with 63% of respondents reporting an increase in revenue after adoption of the technology. However, only 30% of companies apply AI to multiple business units, up from 21% last year.”

While no one argues about the importance and relevance of AI for business outcomes, infusing and scaling AI remains a challenge for most organizations around the globe.

7 Steps to Infuse AI in Your Business

Based on my own experience I would recommend the following steps:

1. Start to Continuously Invest in AI Skills
2. Which Challenges Do You Want AI to Solve?
3. Prioritize AI-Infused Use Cases Based on Business Value
4. Gather AI Expertise (Internal & External)
5. Start a Small AI Pilot to Learn Fast
6. Fuel Your ‘AI Ready Culture’ to Scale
7. Define Your AI Strategy Framework

Step 1: Start to Continuously Invest in AI Skills

To become a leader in benefiting from AI you should invest heavily in AI skills. I would recommend investing within different areas, disciplines and levels of your organization (both for business and for technical roles). The good news is that a lot of online resources are available nowadays, like:

• Microsoft’s AI Business School (with INSEAD) is a freely available on-demand master class series for business leaders that will empower you to be successful and get results from AI: https://www.microsoft.com/en-us/ai/ai-business-school
• OpenAI, for instance “Discovering and enacting the path to safe artificial intelligence” https://openai.com
• Stanford University online lectures, for example “Artificial Intelligence: Principles and Techniques” https://online.stanford.edu/courses/cs221-artificial-intelligence-principles-and-techniques

Spending a bit of time searching the internet will lead to a lot of (often free) online resources about AI, from entry level to niche, deep-dive resources. Considering the speed at which AI develops, continuous learning is crucial.

Step 2: Which Challenges Do You Want AI to Solve?

Brainstorm within a multidisciplinary, diverse team about which challenges you would like to solve using AI. Consider involving partners from your ecosystem and customers. Try to turn ideas into use cases that are very important for your organization. A use case is a specific situation in which a product or service could potentially be used. Scoping use cases will make it easier to understand, experiment, learn and be successful.

Step 3: Prioritize AI-Infused Use Cases Based on Business Value

Business value should be the key to look at. How does each use case score in terms of Attractivity and Feasibility? Attractivity can be assessed in terms of business and financial value (what is the potential upside? How quickly will we benefit?). Feasibility can be assessed in terms of organizational and financial feasibility (e.g. available resources, required investments). Start with a use case that is very attractive and seems feasible.

Step 4: Gather AI Expertise (Internal & External)

Very often, not all required AI expertise is available in-house. Or there is no capacity to focus on the chosen use case. This is perfectly normal. Gather expertise internally and externally. Empower this small team with the autonomy and flexibility to get things done in an agile way. Hire specialists (experts, consultants), involve informal leaders and make sure that they have the mandate and support from the senior leadership team.

Step 5: Start a Small AI Pilot to Learn Fast

A lot of (big) organizations tend to start too big ... The old saying ‘Thing big, start small and scale fast’ still applies. Start a small pilot with a small team to learn (and possibly fail) fast. Make sure that the pilot goals and timeframe are very clear. Speed and agility are crucial in order to be able to reach an AI Ready Culture (see Step 6).

Step 6: Fuel Your ‘AI Ready Culture’ to Scale

Remember: “Culture eats strategy for breakfast” (Peter Drucker). This is all about “leadership behaviors and capabilities required to instill an AI ready culture in your organization” (Mitra Azizirad – Microsoft Corporate Vice President AI Marketing). Becoming an AI-ready organization requires breaking through data- and functional silos. Data-driven, empowerment and inclusion, and leadership and governance are the basis for an AI Ready Culture. Your small AI pilot can be the starting point to start building an enabling, driving and fostering an AI Ready Culture.

Step 7: Define Your AI Strategy Framework

Now that you have some first-hand experience with AI, it’s wise to establish a framework for thinking strategically and holistically about the role of AI in your organization. This is all about thinking strategically about AI and how AI can create value to your business. How will your organization seize the opportunities provided by AI? Starting with an AI Strategy Framework as a first step - without any skills and experience - is often too theoretical in my view.

Next articles

In the next few articles I will show some practical examples of infusing AI by using cognitive services, going from dashboarding to predicting, and applying IoT. From user experience to back-end use cases.

Stay tuned!

Looking forward to your feedback and learnings.

Guido

This is my third article in a series about Data & AI. I write from a business perspective, not technical perspective. I work at Microsoft as a Partner Marketing Advisor (PMA) focusing on Data & AI and Apps & Infra in The Netherlands. This blog is a personal blog written and edited by me. Opinions are my own and not the views of my employer.

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