Picking up new technology in an increasingly digital world is harder than it looks.

More companies may be turning to artificial intelligence, but many have yet to master the transition of integrating A.I. into their business models. As reported by TechTalks, Stanford professor Erik Brynjolfsson recently spoke about some of the challenges that A.I. and machine learning present.

Despite the productivity promises of A.I. technologies, actual efficiency gains are unlikely to be immediate, according to Brynjolfsson. "Often, there's a period where productivity declines, where there's a lull," he explains. "And the reason there's this lull is that you need to reinvent your organizations, you need to develop new business processes."

It triggers a kind of stasis, or what he dubs a "Productivity J-Curve." While time will tell how long the J-curve will last, companies can take steps now to minimize their own lag time. Here are three tips to consider when bringing in new technology:

Don't starve your rollout. 

The technology will improve as more companies adopt it. So, if you want to speed the deployment, invest sooner than later. According to a February research report from Rackspace Technology, more businesses are indeed upping their tech budgets. Nearly 70 percent of those polled said that their company is allocating between 6 to 10 percent of their annual information technology budgets to A.I. and machine-learning initiatives. One year ago, only 30 percent of respondents allocated that much of their budgets.

Start fresh.

Assess your most basic needs to determine what's working versus what's not working, which will help determine compatibility when shopping for new solutions, suggests Dan Ruch, former founder and CEO of corporate travel platform Rocketrip. While you're surely eager to see this tech in action, it's also important not to rush implementation and maintain transparency as problems arise. 

Keep your employees informed.

Communicate with workers to figure out what is and isn't working. That feedback will help you potentially customize the technology according to your needs -- and thus speed (but not rush) its delivery.