Covid-19 accelerated corporate investment in the digitization of customer and employee experience, which is unlike anything I’ve seen in my 25-year career in digital transformation. Large companies took on an average of 20 initiatives costing at least $1 million in 2023 alone, according to the results of our latest research, and decision-makers expect to take on even more of these types of projects in the next few years.
Of course, top of mind for leaders across every industry is the potential that AI holds. AI investment is projected to reach up to $100 billion in the U.S. alone by 2025, according to Goldman Sachs researchers. Yet, many leaders become consumed by the potential of AI without fully understanding it. AI isn’t the first massive technology disruption to drive organizational change, and there will be others. What leaders must do is ask themselves where AI fits within their workforce, operations and broader digital transformation strategy.
Here are five questions to help determine how you should go about your AI strategy.
1. Why do we want to use AI?
Many leaders get consumed by the idea of leveraging AI to evolve their business but stop short of thinking through why their organization needs it. As with any discussion around a new digital or technology initiative, leaders must start with the why. Do you want to automate processes? Are you looking to accelerate product development? Are you trying to generate better insights? If a leader can’t articulate the why behind an AI initiative, then there’s likely misalignment between the rational and the true motivations behind it.
2. What are we going to do with AI?
Once you understand the why, you must consider what your organization is looking to improve or evolve. Do you want to reduce time-consuming processes by automating repeatable actions? Are your developers trying to better identify errors in a code base? Is there a need to identify patterns in a dataset? Is your organization looking to accelerate a product or process development life cycle? All AI initiatives are inherently part of a process. AI doesn’t constitute a standalone function, and it shouldn’t be viewed as a dedicated spend.
3. How are we going to implement AI?
Once you understand the why and the what, only then can you consider how your organization can use insights from AI to better accomplish its goals. How will your people respond, and how will they benefit? Today’s organizations have multiple technology partners, and they may have many that are all saying they can do AI. But how will your organization work with all those partners to make an AI solution come together? Many organizations are developing AI policies to define how it can be used. Having these guardrails ensures that your organization is operating ethically, morally and legally when it comes to the use of AI.
4. Do we have the right data in place?
This is the most important question that leaders fail to ask themselves. We continue to see many organizations challenged with disjointed data despite having large data management initiatives. AI can only be as good as the data you have. Inaccurate data will cause AI to inform bad decisions, and that remains the biggest concern in the marketplace, whether it’s open or closed AI. Data that is incomplete or includes patterns of behaviors that historically occurred based on bad decisions will cause AI to learn those behaviors and provide inaccurate insights.
5. Is our organization ready for operational AI?
People, process and technology are all equally important pillars within the context of any digital implementation, yet organizations often overlook the people and process aspects. Those that over-emphasize technology efficiencies and features may not think through the impact on the end user or on the core operational functionality. It’s important to consider whether your organization is truly ready for AI at an enterprise or divisional level before deciding to implement AI at scale. Pilot projects can help you determine whether the implementation is generating the intended results and better understand how end users will interact with the processes. If you can’t achieve customization and personalization across the organization, AI initiatives will be much tougher to implement.
The world of AI is very broad, and we’re still developing our full understanding of the potential that AI holds at an enterprise level. Yet, it’s clear that the purposeful use of AI to create better insights from the data that an organization owns can have a profound impact on its business. The journey just has to start with taking a step back and asking the right questions at the onset.
In the context of the Industrial Revolution, applying technology to operating mechanisms in each organization is extremely necessary, and is also an inevitable trend to minimize workload while still ensuring efficiency and enhance its competitive position in the market. Furthermore, applying management software into a business will also help build an organization with a clear system, promoting consistency, transparency and accuracy. Tasken eOffice, researched and built by Opus Solution – a business consultant in Vietnam – is an internal work management system as well as the management of automated, online, user-friendly approval processes, allowing businesses to operate more effectively on the path of digital transformation.