As the world of technology makes “always-on” the default, artificial intelligence (AI) and virtual reality (VR) are becoming safe bets for companies looking to invest in tech solutions. They’re two of the most ubiquitous subjects in both B2C and B2B – though consumers are closer to integrating it into their daily routines than businesses. But there are two key factors that keep AI from becoming mainstream in business: data fragmentation and the ever-present struggle for consistent tech adoption.

Too Many Apps, Too Little Communication

AI is a powerful tool with the potential to drive meaningful interactions throughout the sales process. AI’s usefulness to sales and marketing teams requires that it makes it easy for apps to gather data and create unified messaging, and as companies like Salesforce incorporate it into its platforms, more products are following suit.

But adding more apps to a tech stack doesn’t mean salespeople will use them. Research has shown that companies adopting cloud technology still struggle with integration. This leads to companies making major investments in elements of an overall cloud solution that may not work together seamlessly.

The benefit of building a cloud-based tech stack is the ideal of data being pushed and pulled between apps, feeding each solution with the necessary information to work at full capacity. Until all of your tech stack works together, AI will feel disconnected and ineffective.

The Short Shelf Life of CRM Data

There is a significant benefit to storing data in CRM when tech stack solutions communicate with each other. Each action that happens to the technology you own from your employees or clients should begin to update all of the other systems.

Today, however, CRM is too manual for data entry, and the AI on the market today that solves some of the manual data entry for CRM is still far from complete automation. Nothing has been able to completely keep up with constant, daily activity of salespeople, partly because third parties can’t upload information quickly enough to help them make decisions.

If you are thinking about using customer-facing AI, the rate of data decay in your CRM database is about 3 percent every month. That’s the result of regular things like job changes, and does not include the out-of-date lead statuses, unlogged tasks, missing contacts you have interacted with, or inaccurate data from human error. AI needs this data to be accurate to make informed decisions about what to do next; but without clean data, AI is almost useless.

AI certainly has a place in the future of sales, but until the roadblocks of integrations and bad data are cleared away, true adoption will be years away. Once we solve those issues, AI will return time to the daily lives of sales teams and allow them to spend more time on the things that matter. It might even give us a deeper personal connection with the world and people around us.