AI is rapidly becoming a ubiquitous fixture in enterprises worldwide. IDC estimates the AI market to already be worth $28.1 billion in revenue as of 2018.
Although standing shoulder-to-shoulder in the workplace with AI, those wondrous artificial thinkers, may exist only as aspirations for some organizations, know that this market is growing fast. It may not be long before AI tools are as commonplace as mouse pad or monitor in most offices—even yours.
And odds are strong that when the time comes to partner with an AI provider—and start turning AI aspirations into outcomes—IBM will be a frontrunner in your selection.
By the numbers, IDC reports that AI worldwide growth in 2018 reached 35.6 percent, and notably, despite a crowded landscape of competitors, IBM continues to hold the lion’s share of the AI market (9.2%).
Among organizations investing in AI hardware, software, or services, more will buy IBM and rely on Watson than any other vendor. This according to a new IDC report: Worldwide Artificial Intelligence Market Shares, 2018 (full report available here) which names IBM as 2018’s market leader in AI.
So just what sets apart IBM as the leader of the AI provider pack?
In the age of AI’s growing popularity, find below 3 competitive differentiators that make IBM the business world’s first choice in AI.
Robust information architecture
As measured by IDC, IBM revenue generated from AI rose to $2.58 billion in 2018, a 19% increase since 2017. One of the major contributors to this revenue upturn are critical commitments IBM has made to infrastructure; without a solid information architecture (IA) AI initiatives will never be successful.
The typical data environment in many enterprises is sprawled and chaotic—valuable information assets lie trapped in silos that can’t communicate with each other. In fact, according to Forbes, Data citizens spend approximately 80% of their time preparing data for analysis, tasks needed just to get started on the value-add portion of their jobs. IBM Cloud Pak for Data, aided with data virtualization, helps modernize your data estate to manage and ready all your data assets for AI—without moving them. This helps contend with talent shortages, by lessening the time needed for data-prep, and difficulties scaling AI across the enterprise, two of the most pressing AI roadblocks organizations face.
We live in a post-GDPR world. Data privacy is top of mind for not only professionals, but consumers as well, who are filled with general skepticism for information led technologies. A top impediment to AI adoption has proven to be a lack of confidence in the AI model’s accuracy, data quality and integrity, bias management, and fairness.
IBM offers tools to maintain trust and transparency at the genesis of AI: the model. Watson OpenScale works to optimize the modeling development and deployment lifecycle, as well as address bias detection and interpretability to help meet the call for greater explainability of AI technologies. By serving the needs of everyone—not the privileged few—this helps to shed lingering reservations about AI technologies.
As highlighted by IDC, in 2018, IBM AI applications brought to market a line of Watson solutions pretrained to a range of industry verticals and professional use cases including agriculture, HR, CX, supply chain, automotive, manufacturing, and marketing communications.
For organizations looking to buy AI, these applications can rapidly begin operationalizing AI capabilities throughout the business.
IBM also leads market share for AI software platforms as reported by IDC. These are tools designed to help organizations who wish to build their own AI—as well as deploy, optimize, manage, and scale it across their company. This is the optimal choice for organizations eager to begin to develop their own in-house brand of artificial intelligence and start training machine learning models.
More importantly, with the recent acquisition of Red Hat Open Shift, Watson anywhere becomes reality. Enter the world of containerized services: IBM Cloud Pak for Data on Red Hat OpenShift allows Watson microservices to run on a variety of environments from IBM cloud, to any public, hybrid, or multi-cloud environment.
Key solution: Watson Studio, with Cloud Pak for Data on Red Hat Open Shift, deployed anywhere: on-premise, multicloud, or on any cloud you prefer.
Unlock the value in your organization with AI. Visit ibm.com/artificial-intelligence to explore IBM’s Ladder to AI, a prescriptive approach that helps you modernize, collect, organize, analyze and infuse all your data.