It needs to be business strategy that drives the adoption of new technologies rather than the other way round.
Advanced technology has implications that can transform a company’s very nature — from operations, to how people behave, to why leadership makes the decisions they do.
However, the technology’s impact is limiting and potentially damaging if the business doesn’t understand how to apply it strategically.
It’s hard not to get caught up in the excitement of adopting artificial intelligence (AI) and other new technologies that have game-changing potential for the future of the business. The hype sometimes prompts companies to jump in too fast for the wrong reasons, wasting time and money on technology solutions that are not tied directly and strategically to the goals and vision of the business.
New technologies should never drive the adoption of a new business model or strategy; just the opposite, the business strategy must drive the adoption of new technologies.
The problem with chasing the shiny new object is that it puts an emphasis on quick wins rather than sustainable results. This is one of the biggest threats to a transformative culture and it causes companies to ultimately miss the exponential, transformative benefits of connecting digital technologies like AI, blockchain and cyber into an integrated architecture.
And while these technologies can help with day-to-day functionality, they won’t have long-lasting value if they don’t find their way into a broader business strategy.
Instead of racing to adopt the latest technology, businesses first need to adopt a top-down approach that looks at the business model first, and then acquires the capabilities, skill sets and people needed to create that change. In doing so, businesses greatly reduce the risk of making heavy investments in technology solutions that later need to be completely rebuilt. It’s taking a step back to look at the “why” and “how,” instead of just the “what.”
So what does this strategic implementation actually entail?
It all goes back to data. The bottom line is that most organizations aren’t ready to adopt machine-learning technologies since their data sets aren’t clean. Organizing the data is essential to getting the most out of the technology investment and embedding transformation into a company’s DNA.
To get started, companies should begin asking themselves what decisions need to be made to prioritize the data. Next, everyone needs to get on the same page to define the end goals of putting new technology in place. This is where the top-down approach to transformation comes in: what are the customer and employee experiences you’re trying to achieve? How are tools like AI, blockchain and RPA going to help you reach your business goals? It’s critical to consider your risk, return and investment in these planning phases before moving into tactical approaches.
Only when the data has been organized and the objectives have been outlined should companies begin to invest in AI and other automation technologies throughout the entire ecosystem.
As disruption continues in the Transformative Age, having a strategy in place to adopt AI is what will separate the leaders from the laggards. Before you do anything else, focus on cleaning your data — because AI is only as powerful as the integrity of the data it uses to make decisions.
This article was first published on Forbes.com.