IBM Presents “Change the Game: Winning with AI” in New York City

(Note: This blog is part of a multi-part series on this event and the related analyst event focused on IBM’s current status from an AI perspective.)

On September 13th, 2018, IBM held an event titled “Change the Game: winning with AI.” The event was hosted by ESPN’s Hannah Storm and held in Hell’s Kitchen’s Terminal 5, better known as a music venue where acts ranging from Lykke Li to Kali Uchis to Good Charlotte perform. In this rock star atmosphere, IBM showcased its current perspective on AI (artificial intelligence, not Amalgam Insights!).

This event comes at an interesting time for IBM. Since IBM’s public launch of IBM Watson on Jeopardy! in 2011, IBM has been a market leader in enterprise artificial intelligence and spent billions of dollars in establishing both IBM Watson and AI. However, part of IBM’s challenge over the past several years was that the enterprise understanding of AI was so nascent that there was no good starting point to develop machine learning, data science, and AI capabilities. In response, IBM built out many forms of AI including

• IBM Watson as a standalone, Jeopardy!-like solution for healthcare and financial services,
• Watson Developer Cloud to provide language, vision, and speech APIs, Watson Analytics to support predictive and reporting analytics,
• chatbots and assistants to support talent management and other practical use cases,
• Watson Studio and Data Science Experience to support enterprise data science efforts to embed statistical and algorithmic logic into applications, and
• Evolutionary neural network design at the research level.

And, frankly, the velocity of innovation was difficult for enterprise buyers to keep up with, especially as diverse products were all labelled Watson and as buyers were still learning about technologies such as chatbots, data science platforms, and IBM’s hybrid cloud computing options at a fundamental level. The level of external and market-facing education needed to support relatively low-revenue and experimental investments in AI was a tough path for IBM to support (and, in retrospect, may have been better supported as a funded internal spin-off with access to IBM patents and technology). Consider that extremely successful startups can justify billion dollar valuations based on $100 million in annual revenue while IBM is being judged on multi-billion dollar revenue changes on a quarter-by-quarter basis. That juxtaposition makes it hard for public enterprises to support audacious and aggressive startup goals that may take ten years of investment and loss to build.

IBM’s perspective at this “Change the game” event was an important checkpoint in learning more about IBM’s current positioning on AI. Amalgam Insights was interested in learning more about IBM’s current positioning and upcoming announcements to support enterprise AI.

With strategies telestrated by IBM’s Janine Sneed and Daniel Hernandez, this event was an entertaining breakdown of IBM case studies demonstrating the IBM analytics and data portfolio and interspersed with additional product and corporate presentations by IBM’s Rob Thomas, Dinesh Nirmal, Reena Ganga, and Madhu Kochar. The event was professionally presented as Hannah Storm interviewed a wide variety of IBM customers including:

• Mark Vanni, COO of Trūata
• Joni Rolenaitis, Vice President of Data Development and Chief Data Officer for Experian
• Dr. Donna M. Wolk, System Director of Clinical and Molecular Microbiology for Geisinger
• Guy Taylor, Executive Head of Data-Driven Intelligence at Nedbank
• Sreesha Rao, Senior Manager of IT Applications at Niagara Bottling LLC
• James Wade, Director of Application Hosting for GuideWell Mutual Holding Company
• Mark Lack, Digital Strategist and Data Scientist for Mueller, Inc
• Rupinder Dhillon, Director of Machine Learning and AI at Bell Canada

In addition, IBM demonstrated aspects of IBM Private Cloud for Data, their cloud built for using data for AI, as well as Watson Studio, IBM’s data science platform, and design aspects for improving enterprise access to data science and analytic environments.

Overall, Amalgam Insights saw this event as a public-friendly opportunity to introduce IBM’s current capabilities in making enterprises ready to support AI by providing the data, analytics, and data science products needed to prepare enterprise data ecosystems for machine learning, data science, and AI projects. In upcoming blogs, Amalgam Insights will cover IBM’s current AI positioning in greater detail and the IBM announcements that will affect current and potential AI customers.