AI holds tremendous potential to be a disruptive force, but only a small percentage of companies appear to be capitalizing on it, according to recent research published in MITSloan Management Review. The way I see it, what stands in the way of progress for most businesses isn’t what you might expect. Getting started with the technology is often the easy part; the bigger challenge is understanding what AI – and digitization in general — can accomplish.
For many managers, it takes a fundamental shift in thinking to reimagine how AI can unlock new possibilities for their business. To successfully make that shift, here are four tips I often share:
- Think Big – The traditional view of analytics is that it is a vehicle for making incremental improvements in existing business processes or workflows. But that view is short sighted. For example, you might think that adding a predictive insight to a report will help reduce complexities surrounding a workflow. While that’s most likely true, you can achieve more by thinking bigger: what if you could intelligently automate the entire workflow so that the report is no longer needed? Setting your sights higher can put you in position to seize the full potential of AI while also saving valuable time and effort.
- Don’t Wait Until Your Data Is Clean – Many managers mistakenly believe they can’t move forward with AI until their data is squeaky clean. This causes unnecessary delays because, the truth is, there’s no escaping “bad data.” What many people don’t know is that data science has the capability to not only cleanse your existing data, but to also connect it – without the need for expensive tools, platforms and integrations. Even with what might be considered low-quality data, you can begin to build predictive models that generate real business value. Since you will be dealing with a large amount of data, the volume can, in part, compensate for any lack of quality. In the end, what you’ll be able to do is come up with a way to make better business decisions – faster.
- Use Existing Resources – An investment in AI doesn’t have to mean costly new systems and an entire team of new hires. Many companies already have a data infrastructure that can get the job done as well as people with the skills to take on the challenge. Of course, the data may not be accessible across the entire organization, and the people with the ability to perform coding and analytics may not have enough proximity to your most pressing business challenges to adequately address them. The answer is to find ways to make the data broadly accessible and come up with a plan for bringing the right talent into situations where data science stands to have an impact.
- Solve for Scale —If you begin with a goal to build a robot that will take on your company’s biggest and most complex challenges, you’re setting yourself up for failure. Instead, after assembling the right people, identify a scale issue within your business – one that involves a significant volume of steps, transactions or interactions. Also, as you address this challenge, remember that your efforts will serve as a building block for the way your business is able to solve similar problems in the future. One of the biggest advantages of data science and AI is that the more you use them to address a specific problem, the better they get at solving it as time goes on.
As you get started with AI, it’s also essential to remember the reason for implementing it in the first place. For Cisco, that reason is serving our customers better – ensuring their success every step of the way in their journey with us. As we’ve built out our Customer Success practice, we recognized that we needed to engage more effectively with our customers — together with our partners – at scale. Digitization fuels our ability to personalize our communications to customers; predict and prescript what they might need next; and ultimately, help them compete more effectively using our technology.
The benefits for Cisco and our partners are also clear: the more we can do with AI and digitization, the more efficient we can be, and the more our customers will appreciate the many ways we help them work better, smarter and faster.
For more on this subject, I invite you to attend our March 13 webinar, “AI Is the New UI.” Register here.