Watsonx: Can IBM Become a Leader in the Enterprise AI Market in its Second Outing?

Case Code: ITSY141 Case Length: 11 Pages Period: 2010-2023 Pub Date: 2024 Teaching Note: Available

Price: Rs.400 Organization: IBM Industry: Technology & Communications Countries: United States Themes: Artificial Intelligence, New Product Development, Competitive Strategy,B2B Marketing

Abstract Case Intro 1 Case Intro 2 Excerpts

Excerpts

Watson: Ibm’s Foundational AI Tool

In 2004, Charles Lickel, an IBM Research Manager at the time, decided to showcase the company’s expertise in using language learning software. IBM was looking for ways to commercialize and offer this technology to enterprises. Lickel decided to use the developed software to beat a contestant in Jeopardy. This entailed teaching a computer how to beat the game utilizing complicated skills such as language. IBM assembled a team of 15 people and estimated that it would take three to five years to master this new software. This was critical since the e-language was a difficult concept for computers to grasp. By 2010, the new tool was ready and it even competed and won the TV game show in 2011..

Watsonx: Ibm’s Move to Generative AI

In May 2023, IBM announced its entry into the generative AI industry with the intention of reclaiming its former glory with this next-generation technology. The WatsonX platform enabled businesses to develop and configure large language models (LLMs) based on their operational and business requirements. IBM envisioned using this platform to communicate with consumers and employees, streamline corporate workflows, automate IT procedures, improve security, and satisfy sustainability goals. Watsonx included a set of tuning tools for LLMs..

But as it Come too late?

IBM faced stiff competition from both early adopters like OpenAI and latecomers like Elon Musk’s xAI released in 2023. NVIDIA also released AI Foundations for Enterprises in March 2023, which was built on cloud services and allowed businesses to develop big linguistic and visual models based on proprietary information. On the security front, Palo Alto Networks purchased Expanse in February 2023, a generative AI company creating a mechanism for mapping attack surfaces and threat detection. AI security products were also available from OpenAI, Darktrace, Cylance, Deep Instinct, and Symantec..

Next Steps

According to a new Bloomberg Intelligence (BI) analysis, the generative AI market was set to expand and grow to US$1.3 trillion over the next ten years from a market value of US$40 billion in 2022. According to BI’s analysis, growth could accelerate at a CAGR of 42%, led in the short term by training infrastructure and progressively turning to inference devices for large language models (LLMs), digital ads, specialized software, and services in the medium to long term. According to BI, generative AI would grow from less than 1% of total IT hardware, software services, ad spending, and gaming market spending to 10% by 2032. The greatest sources of incremental revenue would be generative AI infrastructure as a service used for training LLMs ($247 billion by 2032), followed by digital adverts powered by the technology ($192 billion), and specialized generative AI assistant software ($89 billion). AI servers ($132 billion), AI storage ($93 billion), computer vision AI goods ($61 billion), and conversational AI devices ($108 billion) would drive revenue in the hardware sector..

Exhibits

Exhibit I: IBM’s revenue -1999-2022 (in billion U.S. dollars)
Exhibit II: Major AI Milestones
Exhibit III: Generative AI Revenue
Exhibit IV: Customer Adoption of Watsonx.data across 4 Key Use Cases

Buy this case study (Please select any one of the payment options)

Price: Rs.400 Instant Download

Price: Rs.400 Express Checkout

PayPal (9 USD)