First, IBM and Salesforce teamed up to tackle enterprise artificial intelligence, partnering to integrate more of IBM’s Watson cognitive computing platform into Salesforce’s products. Now, Adobe and Microsoft are joining forces to expand the AI capabilities of both companies.
The partnership, reports The Motley Fool, is designed to “integrate customer relationship management (CRM) data from Microsoft's Azure cloud and the Adobe Cloud.” In an announcement on its website, Microsoft confirmed that artificial intelligence, in the form of machine learning, was involved:
“Building on both companies’ strong track record in data science and machine learning, Adobe and Microsoft are collaborating on a semantic data model for understanding and driving real-time customer engagement. This model will standardize how data is structured and vastly expedite the process of gaining insights from massive amounts of data.”
Both Adobe and Microsoft have artificial intelligence platforms (Sensei and Cortana, respectively). Now, these systems will be able to access more data than ever before, in a move that both companies hope will significantly improve the outcomes possible with their machine learning algorithms.
In fact, the move to pool data and explore partnership opportunities may indicate, notes Adweek, a potential move to further “the AI arms race as machine learning becomes more understood and accepted.”
“Adobe Sensei is now armed with a new trove of data from Microsoft Dynamics 365, Microsoft Power BI, and Microsoft Azure, from which it can draw on its algorithm-based recommendations. Both companies are also working to add Adobe Sensei to Microsoft tools however, there is no timeline for when this reverse integration will be available.”
What this means is that Adobe and Microsoft are banking that together their data is more valuable than two datasets siloed by product and company. Adobe accesses richer datasets with which to power machine learning insights and recommendations in its marketing platforms. Microsoft potentially fills a gap in its product offerings, and also wins by accessing more data that may help it better serve existing customers.
As an Adobe VP of technology, Anil Kamath, told Adweek:
“At the end of the day, machine learning needs data. It learns from data, and I think having a sort of framework for managing your digital marketing stuff needs to happen before machine learning can play a role.”
If you’re trying to understand AI’s role in marketing, there are some valuable lessons present here.
First, companies with lots of well-organized data stand to benefit significantly from artificial intelligence technologies like machine learning. Kamath is right on the money: the more of the right data that is fed into the right algorithms, the better outcomes machine learning can produce. In Adobe’s case, those types of insights could make its customers’ marketing and advertising campaigns perform better and cost less.
Second, major tech players seem to be addressing the gaps in their artificial intelligence stack through strategic partnerships or purchases. The partnership between Adobe and Microsoft is just one example. Count on seeing others.
These alliances are giving marketers unprecedented access to artificial intelligence in products they may already be using, such as Adobe’s Creative Cloud or Salesforce’s CRM.
Third, marketers need to start becoming comfortable with artificial intelligence, machine learning and related technologies—quick. As Kamath told Adweek: “Everybody needs to have machine learning in order to compete effectively.”
That’s not just idle speculation. The Motley Fool reports that Adobe, in its most recent earnings call, talked about its commitment to train each of its “technical employees in artificial intelligence fundamentals.”
As Chief Content Officer, Mike Kaput uses content marketing, marketing strategy, and marketing technology to grow and scale traffic, leads, and revenue for Marketing AI Institute. Mike is the co-author of Marketing Artificial Intelligence: AI, Marketing and the Future of Business (Matt Holt Books, 2022). See Mike's full bio.