A new generation of point artificial intelligence (AI) solutions will prove themselves within the next year. They’ll build new trust, urgency and an understanding of what AI actually is, and show just how much AI can deliver. Voice-driven solutions will lead the charge. And there’ll be pick-and-place robots in smart warehouses delivering a major competitive edge as companies advance their use of robotic process automation. Here are three key predictions for manufacturing for 2020 and beyond.

The manufacturing sector still has a long way to go to achieve total process automation, but some realistic steps are around the corner—with new technologies driven by artificial intelligence set to move from confusing luxury to proven business tool. AI won’t mean the same thing for every manufacturer, but manufacturers have one thing in common: they can all start somewhere, however small their first steps may be.

Prediction #1:

Fifty percent of all manufacturing companies will be using AI in some form by the end of 2021.
Make no mistake, the implementation of AI solutions will change everything. And everything means every industry, business, process and company. But let’s not forget that for many businesses, targeted AI solutions are already here. They’re already delivering a competitive edge. The year 2020 will be all about that new AI realism spreading, with new targeted, project-based AI solutions hitting the ground running.

AI’s Small Solutions Win Big

A big stumbling block for AI has always been the term AI itself. It misleads many manufacturers, suggesting a large end to end system. In reality, AI is a collection of targeted technologies, from natural language processing to vision identification to chatbots to analytics to automation, each with its own strengths and applications. What these technologies all share is the intelligence factor: a high degree of accuracy and an incredibly fast, smart ability to learn from their mistakes.

That high degree of accuracy is evident at one Northern Europe manufacturer. As a household brand, the company uses an AI demand planning solution to forecast projected consumption in its sector. The accuracy of the forecast before and after the AI solution was a real eye-opener. The demand planning forecast produced by the AI solution proved far, far closer to real market results. And forecast demand planning proved an excellent choice of application. For this business, a concrete, achievable target meant concrete, measurable results.

AI Solutions Are Precision Tools, Not Blunt Instruments

When thinking of AI, you need to remember that you can’t implement AI any more than you can implement the Internet. Before you initiate any project, you must figure out your “why.” What exact business goal and target are you aiming at? What exactly do you want to improve and enhance? The more targeted your objectives, the more competitive and transformative your results.

Prediction #2:

Twenty-five percent of manufacturing planners will be talking to their systems by the end of 2020.
AI solutions are smarter and more eloquent than most people realize. A year ago, a major global AI customer survey found that two thirds of people who said they had never used AI actually had through chatbots. The quality was so high that the chatbots had been indistinguishable from human speech. The same survey found that 84 percent of respondents were comfortable using voice-activated AI at home, in the form of the popular virtual assistant devices. And, if simplicity, speed and accuracy are crucial consumer benefits, imagine what they could do on a manufacturing line.

The smart integration of virtual assistants in cars by certain auto makers is being widely applauded. And rightly so. The integrated voice activation goes way beyond skin deep, adding layers of service and performance capability to the whole driving experience. What’s less well-known is that voice-activated solutions are also already being used on the production side of the automotive sector.

In Japan, companies are already using voice-activated solutions in their order picking process, where line personnel simply give spoken instructions and their order is instantly created.

Prediction #3:

Pick-and-place robots will put away 25 percent of manufactured goods by the end of 2020.
Robots on production lines have been essential for decades. But what kind of savings and competitive edge will AI-enabled robots in the warehouse deliver? With big e-commerce companies making headlines with their smart warehouses staffed with swift, inexhaustible robots, it is clear that robots raise the performance and savings bar in a huge way. With no eyes or flesh, robots do not need lighting or heating, so energy costs plummet. There are no time or weight limits on breaks, shifts, or loads. And the flexibility, fluency, reach and economy of robot-driven picking and placing means no wasted time or effort—and far better utilization of space. Twenty-four hour, fully automated warehouses will be able to store and do more, without having to get bigger.

And, as it is with AI, so it is with robots. It’s already happening, with small, targeted use cases that will keep growing bigger. For example, several North American companies are extending their use of robotics from loading boxes to complete material handling. For some, it’s another small step on their longer journey to digital transformation.

Although full lights-out warehouses may be some years away, it has begun. Innovative companies are already beginning work with automated warehouses. Heavy parts that may have once required a team of workers can now be plucked off the shelf by one robot with no wasted effort, no wasted time and no additional costs.

Take the First Steps to AI

In 2020, you will see the technologies in all these predictions gaining traction in the world of business. They will become more targeted and more project-driven. They will be more focused on achieving small, concrete improvement results that will lead to big change.

For many companies, 2020 will be the year when they realize they don’t actually need to climb an AI mountain. They just have to keep taking the right, small steps. By doing that, they will still be able to reach new heights.