IBM is gearing up to expand its channel initiatives surrounding the IBM Watson artificial intelligence (AI) platform now that IBM has committed to making those technologies available on multiple public clouds.
Previously, the IBM Watson strategy revolved around trying to convince customers to move data on to an IBM Cloud platform where Watson algorithms could be then applied. That strategy met with mixed success, especially as it became apparent that customers were intent moving massive amounts of data on to public cloud where Amazon Web Services (AWS), Microsoft and Google are already making available large numbers of machine and deep learning algorithms.
As IBM moves to make various offerings branded under the Watson moniker available on multiple public clouds, the Watson channel program will need to be extended to appeal to independent software vendors (ISVs) and systems integrators that have developed applications and solutions for those public clouds, says Wes Chung, director of Watson Business Applications.
“We’re looking for partners to create new use cases,” says Chung. “We need partners to bring us into new areas.”
As part of that effort, Chung says IBM is also committing to making the Watson application programming interfaces APIs simpler to consume.
Despite all the hype surrounding AI, it turns out that only 14% of organizations have managed to deploy one or more AI-based projects in a production environment. AI challenges that need to be overcome span everything from ensuring the data being used to drive the AI model is accurate to a lack of skills and formalized processes for inserting AI models into applications.
As a result, the opportunity surrounding AI from a channel partner perspective is still relatively nascent. IBM is betting by making its extensive portfolio of Watson AI technologies available on multiple clouds it will be able to differentiate itself from algorithms provided by cloud service providers that are optimized for a single platform. That approach could prove to be especially attractive to ISVs that need to deploy instances of their applications across multiple clouds.
Of course, the challenge ISVs will face when partnering with the breath of IBM AI portfolio, which already includes applications to address a range of vertical industries. Chung says there’s still plenty of opportunity for partners in each of those market segments and that IBM is committed to providing partners with a product road map that makes it clear where IBM’s AI ambitions lie.
At this juncture, it’s clear just about every application is going to be infused with machine and deep learning algorithms. The issue partners face now is determining the timeframe around which use cases are likely to generate the biggest opportunities soonest.
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