2023 will be remembered as a pivotal year for AI. After OpenAI introduced ChatGPT in late 2022, there was an overwhelming wave of excitement surrounding generative AI in all its forms. Many technology companies eagerly jumped on the hype train, driven by mandates from their boards of directors to "make something happen. " But amidst the hype, there were tangible advancements as well. Companies like Adobe and Zoom showcased AI products that made a significant impact in their respective markets. IBM stands firmly in the camp of substantial progress, given its extensive AI research and development program, long-running history, enterprise-first approach, and the rapid deployment of its AI products. Notably, IBM's recent launches of the watsonx platform and Granite AI models mark significant milestones. Additionally, IBM has been assisting numerous clients across various industries in implementing AI for human resources, customer experience, application modernization, and more. This goes beyond mere participation in the AI trend – it represents tangible progress and transformative developments. IBM's renowned achievements in AI, such as the victories of Deep Blue in a chess match against Garry Kasparov in 1997 and Watson defeating Ken Jennings on Jeopardy in 2011, are well-known. These accomplishments were not simply for show, as IBM quickly applied these technologies in areas ranging from cancer treatment to retail optimization. Five years ago, Rob Thomas, the former head of IBM Analytics and current Chief Commercial Officer, advocated tirelessly for companies to conduct small and large-scale experiments in utilizing AI to serve customers and solve business problems more effectively. These efforts were extensively covered by analysts, like myself, who recognized that AI had the potential to transform numerous areas of work. While GAI (generative AI) has dominated the conversation over the past 15 months, it is essential to acknowledge that technology leaders, including IBM, AWS, and Google, continue to make progress in other aspects of AI. IBM, in particular, has leveraged its watsonx AI and data platform, launched in May 2023, which encompasses not only GAI but also machine learning, deep learning, and foundational models. Within this platform, watsonx. ai serves as an AI studio supporting all stages of AI development and deployment, watsonx. data functions as an open data lakehouse optimized for AI, and watsonx. governance ensures trust, accountability, and transparency in AI processes and projects by capitalizing on IBM's extensive data governance expertise. With the flexibility to accommodate diverse functions, from cutting-edge data science to optimizing financial portfolios, marketing campaigns, or supply chains, the platform can automate specific tasks such as software coding and compliance reporting, leading to significant cost and time reductions. IBM continues to improve the platform, incorporating technical enhancements like new vector database features and introducing its Granite series of GAI models. These models are trained on carefully curated datasets from internet, academic, code, legal, and finance domains, enabling enterprise applications and workflows. Furthermore, IBM allows customers to pair these models with their own data for customized models, amplifying insights, informed decision-making, and personalized customer responses. Benchmark data from IBM demonstrates that tailored models enhance accuracy, relevance, and price-for-performance, offering customers the best outcomes. The watsonx platform and AI models are part of IBM's broader GAI stack, which benefits from the company's extensive expertise in areas such as OpenShift, data services, and integrations.

They are further supported by IBM Consulting and its extensive network of system integrators and partners. Recognizing the importance of collaboration, IBM has recently formed partnerships with SAP, AWS, Adobe, Microsoft, Salesforce, and others to accelerate the adoption of enterprise AI solutions. IBM's commitment to customer satisfaction is evident in its provision of full indemnification for its models, a compelling selling point for enterprise customers. The training data of these models undergoes rigorous filtering to address concerns related to privacy, bias, and objectionable material while upholding high standards of transparency and explainability – a reflection of IBM's comprehensive approach to AI governance. IBM's emphasis on responsible AI usage aligns with the efforts of industry peers like Adobe and Salesforce, who also prioritize responsible AI implementation through IP indemnity and trust layers, respectively. In addition to these initiatives, IBM co-founded the AI Alliance alongside Meta, aiming to promote open innovation, enhance safety, and foster security and trust in AI. With over 70 global members, including universities, agencies, nonprofits, startups, and major tech companies like AMD, Dell, Intel, and Oracle, the AI Alliance seeks to unite computational power, data, tools, and talent to foster open-source innovation in AI software, models, and tools. It's worth noting that certain major AI players, including Amazon, Google, Microsoft, Nvidia, and OpenAI, are not currently part of the AI Alliance. Whether these leading firms in the AI sector will eventually converge on matters of collaboration, governance, and related areas remains to be seen. While IBM faces significant competition from major technology companies with greater resources, its long-standing expertise in AI, domain-specific knowledge, and comprehensive approach to scaling AI solutions for real-world problems position it favorably in this new era. IBM's commitment to technology, speed of change, service, product time-to-market, and partnerships across system integrators, independent software vendors, and major cloud service providers signifies a new and improved IBM. Despite the company's important, albeit different, past, it should not be overlooked. Whether an enterprise, partner, or investor, it is advisable to take a fresh look at IBM. I have been closely tracking IBM for decades, and the energy, excitement, and execution surrounding its AI endeavors, both from IBM itself and its customers, are truly remarkable. IBM is not solely targeting isolated challenges but is envisioning the potential for broad enhancements across business functions like talent acquisition/management, customer service, and software development. The possibilities include a 40% improvement in overall HR productivity, AI assistants handling over 90% of customer inquiries, and up to 60% of software development content being automatically generated by AI. These advancements exemplify how AI will fundamentally transform the business landscape, extending to entire industries and redefining career categories. While IBM faces challenges in realizing its AI ambitions, particularly in the face of fierce competition, its longstanding AI history, domain expertise, and comprehensive approach to scaling AI for practical use make it well-positioned for success in this new era. To conclude, these recent developments paint a compelling picture of a new IBM characterized by technology focus, agility, and strategic partnerships. I highly recommend taking a fresh look at IBM and its expanding AI capabilities, as it exemplifies a company embracing the potential of AI to drive real-world impact.