Global business leaders are virtually united in the conviction that artificial intelligence (AI) will deliver its best advantages when it’s used to supplement—rather than supplant—human ability. In other words, your team and tech will be infinitely better together.
Emblematic of that concept is the fact that, as numerous studies have shown, successful AI implementation is dependent on human engagement. With that in mind, let’s consider a few of the challenges hampering AI integration today, along with smart strategies for overcoming them:
Change Management
A huge percentage of failed AI deployments can be attributed to a lack of personnel buy-in. Employees—from rank-and-file to management—can feel threatened by AI, either perceiving it as a replacement that will take over their jobs or fearing they will be unable to keep pace with the new skills and other changes required by the initiative. The best AI in the world can’t do anything for your company if your people aren’t willing and able to use it.
Communication is key to getting every employee invested in the implementation. They need to understand what’s happening and why – and that ‘why’ should cover not only how AI will benefit the organization, but how it will help every team member work better, smarter, faster, and easier. They must be reassured that they will be upskilled and reskilled as needed, how that will happen, and how, contrary to their concerns about becoming redundant, those skills will enrich and empower their career paths.
Cost
The cost of AI technology is decreasing, with many partners now offering models that reduce the initial financial burden. What’s even more important than the monetary outlay, though, is being able to establish a substantial return on investment that will make the cost, in terms of not just money, but time and effort, worth it.
This is one of the many reasons the whole team needs to be on board, identifying areas where AI can make a positive, palpable impact, from increased efficiency to improved customer satisfaction to decreased agent attrition. Customer experience (CX) agents will know what customers are looking for better than anyone else, while operations managers offer an unmatched awareness of process bottlenecks and pain points. Once these specialists have weighed in, leaders can select the right high-volume, low-complexity tasks to start with, in order to quickly demonstrate value and evaluate success or failure.
Data Readiness
Another significant hurdle to the success of AI implementation has been data, which, prior to AI initiatives, has often been outdated, inaccurate, incomplete, or siloed, with departments—whether intentionally or unintentionally—keeping certain information to themselves. For AI to function correctly, an organization’s data must be cleaned, unified, organized, and labeled – a monumental endeavor that requires the entire team’s effort.
This, however, should be viewed less as a problem and more as an opportunity, not just to optimize the company data pool, but to get everyone working together, in concert. It’s not just a matter of dumping all the data on the IT department and expecting them to make it work – this is an opportunity for every department to specify what data they typically need access to and how they need to work with it. The smart play is to begin with a contained project where you have full data control, thereby proving the concept before scaling it fully.
All these examples show how organizations need humans to make AI work, so that, once integrated, AI can help humans work better.
