A Five-step Approach for Successfully Navigating AI

A Five-step Approach for Successfully Navigating AI

Ulrika Mann

Ulrika Mann,

Incorporating artificial intelligence into your business systems and processes is a journey unlike any other digital technology implementation. We suggest a five-step process for navigating it successfully.

Businesses are learning to use new AI technologies – everything from chatbots to neural networks – to create personalized experiences, intelligent products and smarter business processes. However, unlike other scalable technologies such as cloud and analytics, AI requires a fresh look at every use case. To ensure AI efforts achieve their desired business outcomes, we recommend the “5 E” process:

  1. Educate up and down the organization. Fulfilling AI’s potential means knowing how to apply it to the right business problems and processes. Despite the buzz, confusion remains over even the basics of AI. AI requires its own literacy. For example, how does an advanced form of AI such as machine learning (ML) differ from other forms of the technology? (See Quick Take, below.) In addition to these distinctions, it’s important to understand that AI forms a continuum: There is no start or end, and it’s the combination of tools and techniques, applied to the right business problems and processes, that will deliver personalized experiences with efficiency and scale.
  2. Embrace experimentation. With AI, openness to new business needs is as important as trying out new technologies and techniques. In AI, experimentation begins with the willingness to view data holistically. What’s the underlying root cause for the findings? How can the attributes be tracked in the system? Businesses need to rethink how work is done, identify the new business structures needed to support this work, and spot the resulting opportunities to grow revenue and improve performance.
  3. Evaluate. Are the AI pilot results definitive? What’s the next phase for AI within the organization? Because nearly every organization is still learning how to apply AI, it’s easy to get lost in the evaluation process. The key is to create a nimble organization in which all stakeholders – business owner, process owner, data owner and technology owner – come together to experiment with business outcome-focused use cases.
  4. Establish priorities. Given AI’s growing profile, determining the projects that offer real business value is a key step for organizations. Which pilots share a common AI core that all functions can leverage? Which ones can the larger company learn from? The end goal is to establish AI as a capability that the organization as a whole can embrace.
  5. Explore further. Building out AI as a capability means tackling thorny questions such as whether to focus AI efforts within a single functional area or apply them broadly across the company. The important part of this step is for companies to consider how they can better organize themselves around AI. What processes can they create that are useful for applying their AI learnings to other parts of the organization?

To summarize, businesses can develop a mindset that will instill success by educating their workforce on AI, embracing experimentation, understanding how to evaluate AI pilots, determining project prioritization, and pushing AI insights further into the organization. While each business will take its own path to AI, all organizations can follow this process to optimize business results.