I made some predictions about Artificial intelligence back in January, and I wasn’t alone in stating that AI is likely to become the next transformational technology on the horizon for marketers, and the sales teams we support. I’ll go so far as to say I think AI could become as ubiquitous as the telephone or computer.

This prediction isn’t too much of a stretch. Artificial Intelligence (AI) is already advancing so quickly that computers can learn specific tasks without being programmed to do so, and many experts are predicting it will become integral in marketing and marketing automation systems.

Forbes contributor and marketing expert Andrew Stephens recently stated what we’ve been thinking: “Marketers have more insights-related tools at their disposal that facilitate true data-driven decision making, but AI is needed to help integrate across tools, datasets, and platforms.”

With all the data, analytics software, marketing tools, and marketing technology software out there—we estimate it’s now 5,000 tools and growing—keeping track of and integrating this data will be increasingly more complicated and difficult. That’s where AI fits in. AI will enable companies to integrate data and information seamlessly from all systems, making it easier for disparate marketing tools to work together.

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DiscoverOrg is a provider of data to sales and marketing teams, so we focus on the accuracy, efficacy, and use of that data. Already, AI is poised to support and augment companies like ours. How will this new machine learning technology affect B2B sales, relationships, and marketing?

Based on what we’re seeing within our business and elsewhere, we believe AI will make the strongest impact in four areas:

Data Accuracy & Availability

Data is key to AI technology. While AI initially uses data to respond to human inputs, it evolves independently to generate its own instructions through the process of machine learning—no human needed—unless errors arise. For accurate results, it’s critical that datasets are accurate, complete and very large.

Here’s why: A computer algorithm can’t tell if the data input is correct or incorrect.  It learns and evolves based on whatever information it is fed, so if the information is inaccurate or incomplete, the downstream results can be deeply flawed.

Conversely, this issue also becomes increasingly true if the dataset is small: small errors and inconsistencies take on outsized influence. So, as much as we view AI may as the wave of the future, it needs access to a tremendous amount of data to ‘learn.’

According to Computerworld, “In fact, the artificial intelligence boom is as much about the availability of massive data sets as it is about intelligent software. The bigger the data sets, the smarter the AI. One important area of AI innovation is: How do you get enough data?”

Clearly, larger companies will be at an advantage here, because they are more likely to have large datasets available. But the quality of the learning from these large datasets will be entirely dependent on the accuracy and completeness of the data.

Also Read: Marketers Must Leverage Unstructured Data

Data Management

Because of data availability will be so critical, many companies will shift their focus from sales development to data management. Like all emerging technology, jobs will change or disappear completely, as we saw in the automated industrial revolution, and companies will create jobs around AI.

In fact, the Forbes article “Artificial Intelligence Will Change the Job Landscape Forever. Here’s How to Prepare”  quotes a PwC study that says 38% of jobs in the U.S. are at high risk of being replaced by AI over the next 15 years. That’s the bad news.

The good news is that new, high-demand data management positions will be created. Because AI relies so heavily on the accuracy and efficacy of monstrous amounts of data, experts in this field will become more and more important.

Indeed, the growth of database administrator jobs is projected to outpace all other occupations, growing 11 percent between 2016 and 2026, according to the Bureau of Labor Statistics. Growth in this occupation will be driven by the increased data needs of companies across the economy.

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Relevance and Trust—With a Caveat

Due to its ability to adapt and interpret patterns and data so quickly, AI predictions will be trusted as much as top-level C-suite executive recommendations.

Those predictions will become commonplace in major decision-making meetings and strategies, but because AI trains the algorithms within sales and marketing tools, among others, those CRM/MAT datasets must be as accurate, complete, and ingestible as possible.

An IDC white paper recently estimated the big data global market at $136 billion per year in 2016. On the flip side, IBM projected the yearly cost of poor quality data at $3.1 trillion in 2016 in the U.S. alone, according to Harvard Business Review.

IBM isn’t alone in its dismal view of available data today. Experian Data Quality estimates bad data impacts the profitability of 88 percent of all American companies.  Its research notes that “U.S. organizations believe 32 percent of their data is inaccurate–a 28 percent increase over last year’s figure of 25 percent.  This high degree of inaccurate information causes 91 percent of respondents to believe revenue is affected by inaccurate data in terms of wasted resources, lost productivity, or wasted marketing and communications spend.”

Because of the expected importance of AI in major decision making for companies, improving the accuracy of data quality will be paramount for businesses globally. 

Also Read: 3 Pivots Marketers Need to Make to Improve Marketing Performance

Sales and Marketing Relationships

That statement may sound like an oxymoron, but new research suggests that AI may actually give sales and marketing employees a better chance to connect with clients on a personal level. According to McKinsey Global Institute, 40% of time spent on sales-related activities can be automated by AI.

Using AI to manage CRM databases, B2B apps, sales automation software and more will eliminate the time spent by sales employees dealing with those complicated tasks.

So, while AI handles the mind-numbingly tedious, detail-oriented tasks like analytics and app management, sales and marketing teams can actively pursue “human interactions” with clients, leading to higher job satisfaction and deeper, mutually beneficial relationships. And that’s the best AI prediction of all.

Also Read: What Pixar Can Teach Us About AI & Machine Learning