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Five questions to decide where AI fits in your digital transformation strategy
Five questions to decide where AI fits in your digital transformation strategy
The COVID-19 pandemic has accelerated corporate investments in digitalization unlike anything I have seen in my 25-year career in digital transformation. According to our latest research, in 2023 alone, large companies will undertake an average of 20 initiatives, each costing at least $1 million. Policymakers expect to undertake more similar projects in the coming years. This shows that companies are paying more and more attention to the digital experience of customers and employees and will continue to invest to adapt to changing market needs.
# Of course, what leaders in every industry are most concerned about is the potential held by AI. Goldman Sachs researchers predict that by 2025, AI investment is expected to reach $100 billion in the United States alone. However, many leaders get carried away by AI without fully understanding its potential. AI is not the first large-scale technological disruption to drive organizational change, and there will be other technological disruptions in the future. Therefore, leaders must ask themselves where AI fits within their workforce, operations and broader digital transformation strategy. They need to develop a deep understanding of AI’s strengths and limitations and determine how it can be integrated with existing business and strategic goals. In addition, leaders should also actively cultivate AI experts within the organization and cooperate with external partners to accelerate the implementation and application of AI. Through these efforts, leaders can better seize the opportunities presented by AI and turn them into competitive advantages for their organizations.
Here are five questions to help you determine how you should implement your AI strategy.
1. Why should we use AI?
Many leaders are consumed by the idea of leveraging AI to grow their business, but fail to think about why their business needs it. As with any discussion around a new digital or technology initiative, leaders must start with why. Do you want to automate processes? Do you want to speed up product development? Are you trying to generate better insights? If a leader cannot clearly articulate the rationale and real motivation behind an AI initiative, then There may be deviations between them.
2. What will we do with AI?
After understanding why, you must consider what it is that your business hopes to improve or develop. Are you looking to reduce time-consuming processes by automating repeatable actions? Are your developers trying to better identify bugs in your code base? Do you need to identify patterns in a data set? Does your business want to speed up a product or process? Development life cycle? All AI initiatives are inherently part of a process. AI does not constitute a standalone function, nor should it be viewed as a specialized expense.
3. How will we implement AI?
Once you understand the why and the what, you can then consider how your business can use insights from AI to better achieve its goals. How will your employees respond, and how will they benefit? Enterprises today have multiple technology partners, and they probably have a lot of them saying they can do AI. But how will your business work with all these partners to bring AI solutions together? Many businesses are developing AI policies to define how AI will be used. With these guardrails in place, ensure your business is ethical, ethical, and legal when using AI.
4. Do we have the right data?
This is the most important question that leaders fail to ponder. We can see that despite having large data management programs, many organizations still face the challenge of data disconnect. AI can only perform as well as the quality of data it has. Accurate data is key to ensuring that AI provides good decisions, which is the biggest concern in both open and closed AI fields. Incomplete data or data that contains historical patterns of behavior based on poor decision-making can cause AI to learn these behaviors and give inaccurate insights.
5. Is our enterprise ready to operate AI?
In the context of digital implementation, the importance of people, processes and technology cannot be ignored. However, many companies tend to focus too much on technical efficiency and functionality, while neglecting people and process issues. This can lead to situations that negatively impact end users and core operational functions. Therefore, before deciding whether to implement artificial intelligence on a large scale, you must ensure that your business or department is ready. Pilot projects allow you to evaluate whether the implementation is working as expected and to better understand how end users interact with the process. Implementing AI initiatives will become more difficult without enterprise-wide customization and personalization. Therefore, preparations in terms of people and processes must be fully considered before moving forward with an AI project.
The world of AI is undoubtedly vast, and we are continuing to deepen our understanding of the potential of AI at the enterprise level. What is clear, however, is that the purposeful use of AI to extract better insights from enterprise data can have a profound impact on business. To ensure success, we need to start the journey by taking a step back and asking the right questions.
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