Close Menu
  • Home
  • AI Models
    • DeepSeek
    • xAI
    • OpenAI
    • Meta AI Llama
    • Google DeepMind
    • Amazon AWS AI
    • Microsoft AI
    • Anthropic (Claude)
    • NVIDIA AI
    • IBM WatsonX Granite 3.1
    • Adobe Sensi
    • Hugging Face
    • Alibaba Cloud (Qwen)
    • Baidu (ERNIE)
    • C3 AI
    • DataRobot
    • Mistral AI
    • Moonshot AI (Kimi)
    • Google Gemma
    • xAI
    • Stability AI
    • H20.ai
  • AI Research
    • Allen Institue for AI
    • arXiv AI
    • Berkeley AI Research
    • CMU AI
    • Google Research
    • Microsoft Research
    • Meta AI Research
    • OpenAI Research
    • Stanford HAI
    • MIT CSAIL
    • Harvard AI
  • AI Funding & Startups
    • AI Funding Database
    • CBInsights AI
    • Crunchbase AI
    • Data Robot Blog
    • TechCrunch AI
    • VentureBeat AI
    • The Information AI
    • Sifted AI
    • WIRED AI
    • Fortune AI
    • PitchBook
    • TechRepublic
    • SiliconANGLE – Big Data
    • MIT News
    • Data Robot Blog
  • Expert Insights & Videos
    • Google DeepMind
    • Lex Fridman
    • Matt Wolfe AI
    • Yannic Kilcher
    • Two Minute Papers
    • AI Explained
    • TheAIEdge
    • Matt Wolfe AI
    • The TechLead
    • Andrew Ng
    • OpenAI
  • Expert Blogs
    • François Chollet
    • Gary Marcus
    • IBM
    • Jack Clark
    • Jeremy Howard
    • Melanie Mitchell
    • Andrew Ng
    • Andrej Karpathy
    • Sebastian Ruder
    • Rachel Thomas
    • IBM
  • AI Policy & Ethics
    • ACLU AI
    • AI Now Institute
    • Center for AI Safety
    • EFF AI
    • European Commission AI
    • Partnership on AI
    • Stanford HAI Policy
    • Mozilla Foundation AI
    • Future of Life Institute
    • Center for AI Safety
    • World Economic Forum AI
  • AI Tools & Product Releases
    • AI Assistants
    • AI for Recruitment
    • AI Search
    • Coding Assistants
    • Customer Service AI
    • Image Generation
    • Video Generation
    • Writing Tools
    • AI for Recruitment
    • Voice/Audio Generation
  • Industry Applications
    • Finance AI
    • Healthcare AI
    • Legal AI
    • Manufacturing AI
    • Media & Entertainment
    • Transportation AI
    • Education AI
    • Retail AI
    • Agriculture AI
    • Energy AI
  • AI Art & Entertainment
    • AI Art News Blog
    • Artvy Blog » AI Art Blog
    • Weird Wonderful AI Art Blog
    • The Chainsaw » AI Art
    • Artvy Blog » AI Art Blog
What's Hot

From Static Products to Dynamic Systems

Dual AI engines: LLMs and optimizers sweep September mega-round funding

'Western Qwen': IBM wows with Granite 4 LLM launch and hybrid Mamba/Transformer architecture

Facebook X (Twitter) Instagram
Advanced AI News
  • Home
  • AI Models
    • OpenAI (GPT-4 / GPT-4o)
    • Anthropic (Claude 3)
    • Google DeepMind (Gemini)
    • Meta (LLaMA)
    • Cohere (Command R)
    • Amazon (Titan)
    • IBM (Watsonx)
    • Inflection AI (Pi)
  • AI Research
    • Allen Institue for AI
    • arXiv AI
    • Berkeley AI Research
    • CMU AI
    • Google Research
    • Meta AI Research
    • Microsoft Research
    • OpenAI Research
    • Stanford HAI
    • MIT CSAIL
    • Harvard AI
  • AI Funding
    • AI Funding Database
    • CBInsights AI
    • Crunchbase AI
    • Data Robot Blog
    • TechCrunch AI
    • VentureBeat AI
    • The Information AI
    • Sifted AI
    • WIRED AI
    • Fortune AI
    • PitchBook
    • TechRepublic
    • SiliconANGLE – Big Data
    • MIT News
    • Data Robot Blog
  • AI Experts
    • Google DeepMind
    • Lex Fridman
    • Meta AI Llama
    • Yannic Kilcher
    • Two Minute Papers
    • AI Explained
    • TheAIEdge
    • The TechLead
    • Matt Wolfe AI
    • Andrew Ng
    • OpenAI
    • Expert Blogs
      • François Chollet
      • Gary Marcus
      • IBM
      • Jack Clark
      • Jeremy Howard
      • Melanie Mitchell
      • Andrew Ng
      • Andrej Karpathy
      • Sebastian Ruder
      • Rachel Thomas
      • IBM
  • AI Tools
    • AI Assistants
    • AI for Recruitment
    • AI Search
    • Coding Assistants
    • Customer Service AI
  • AI Policy
    • ACLU AI
    • AI Now Institute
    • Center for AI Safety
  • Business AI
    • Advanced AI News Features
    • Finance AI
    • Healthcare AI
    • Education AI
    • Energy AI
    • Legal AI
LinkedIn Instagram YouTube Threads X (Twitter)
Advanced AI News
IBM

IBM’s Transformation–From Survival To Success

By Advanced AI EditorAugust 16, 2025No Comments6 Mins Read
Share Facebook Twitter Pinterest Copy Link Telegram LinkedIn Tumblr Email
Share
Facebook Twitter LinkedIn Pinterest Email


It is hard to watch what many companies are going through today. Automakers, the news media, entertainment industry businesses, banks and other financial institutions–they and others are being seriously challenged by market forces, technology shifts and the changing dynamics of a global economy. Some of them are fighting for their very survival.

At my company we know what that is like. We have been there.

If you go back about a quarter of a century,
IBM

was at the pinnacle of success. Over the previous two decades we had practically invented general-purpose computing for business. We had helped put a man on the moon. Our researchers won Nobel Prizes. Our revenue and market share skyrocketed as customers clamored for our latest products. By 1984 we were the toast of Wall Street.

Less than a decade later, we were toast. In 1993 we posted what at the time was the biggest loss in the history of corporate America, $8 billion. We had missed a number of key technology shifts. Customers who had previously said “no one ever got fired for buying IBM” were abandoning us for faster, more nimble competitors. One major business publication labeled us a dinosaur. Another said our era had passed.

Finding our way back to growth and success was a difficult and painful process. But it illustrates that companies on the brink can turn things around if they do what is necessary. So I would like to share a few lessons we learned from our near-death experience and rebirth.

1. Businesses must be genuinely global. Technological advances and globalization have completely changed the rules about how and where things can and should get done, yet many companies still cling to their old models for operating, duplicating the same functions and organizations in various locations. This leads to layers of complexity, discrepancy and redundancy that produce a significant drag on efficiency and performance.

We were operating on a multinational model, with mini-IBMs in most of the countries we operated in–IBM Japan, IBM Canada, IBM France, IBM Argentina, etc. Many had their own local manufacturing and delivery operations. Each country had its own unique profit-and-loss statements, its own legal and human resources departments, its own information technology and financial systems, and so forth.

Because of our global reach and advances in technology, we were able to move past that and adopt a shared-services model that allowed us to strip away a lot of that cost and complexity while also better using our resources and talent. We adopted standard processes and reporting procedures for all our internal functions and consolidated those activities in key centers.

We also adopted this approach to how we develop, deliver and support our products and services. This allowed us to tap the best talent and resources wherever they resided, be it in Bangalore, Brazil, Bratislava or Boulder, to run our business and serve clients around the world. This model has allowed us to lower our shared-services costs by about 25% over the last five years.

It also ensures that nine out of 10 IBM employees now focus on developing, producing and delivering high-value solutions for our clients rather than servicing the internal workings of IBM. And operating as a global business means that even our teams in small growth markets can tap IBM’s talent pool to deliver value for their clients.

2. Sometimes companies must fully transform their portfolios. Companies in a crisis need to look at their entire portfolios, rationally and candidly, and figure out what they have that customers want today and what customers will want tomorrow. Then get rid of anything that does not fit the resulting model, and invest in the growth opportunities.

In our case, the information technology industry was rapidly becoming commoditized, and we determined that we needed to shift our portfolio to a more balanced mix of high-value offerings. That meant growing our services and software businesses, both through internal investments and through acquisitions. We have acquired more than 200 companies at a cost of $30 billion to help fill out our portfolio of products and services in these strategic growth areas, such as our growing analytics business.

It also meant divesting low-growth, low-margin product lines and technologies like memory chips, technology components, printers, displays and personal computers. This was easier said than done, as those were technologies, products and even whole markets that we had invented and developed.

In a case like this where a company is struggling to survive, it is easy to understand and accept such change intellectually. It is much harder to grasp it culturally, because of the institutional significance these offerings can have.

3. Success comes from leadership, not mere survival. The people running some companies may be inclined, at least initially, to resist the tremendous economic, social and technological forces of change they face. We have seen evidence of this approach–and its devastating results–across the range of industries I mentioned at the outset. But the only thing anyone ever accomplished by standing in the way of progress was to get run over. The path to success lies in understanding the relevant trends, figuring out how your strengths and resources can capitalize on them and staking out a leadership position.

Depending on your industry, the result could be high-efficiency, low-emissions vehicles, developing new models for profitably delivering digital content to your audience or creating new investment instruments that provide both transparency and competitive returns.

For us it meant understanding the growth of the Internet in the mid-1990s and then helping our clients harness it for their businesses, with our eBusiness and On Demand initiatives. We have evolved along with a world where computing technology is now embedded in almost everything–automobiles, cellphones, shipping containers, manufacturing plants, public works, utility systems and more–allowing users to gather and share a tremendous amount of data.

So we are helping our clients capture and analyze all that data and extract meaning from it to make better decisions, reduce costs, improve efficiency and lower environmental impact, an initiative we call “smarter planet.” Overall, the goal is to get to the front first, set the tone and content for the conversation and lead the way for your clients and your industry.

Conclusion

I share these experiences and examples as a reminder that changing times can imperil even the most successful companies. And I also share them to show that troubled companies can find their way back if they are willing to reinvent themselves in ways that will make them viable and relevant in today’s global economy.

But to achieve this, you must accept that complacency is a business killer and banish it from your thinking. You must understand that transformation is a constant and continuous process that can never end. And you must embrace the notion that when faced with tough times your goal must be not merely to survive but to succeed, and success comes through leadership.

Bridget van Kralingen is general manager for IBM North America, where she is responsible for strategy, execution, business results and client satisfaction for the full range of IBM’s business in the United States and Canada.



Source link

Follow on Google News Follow on Flipboard
Share. Facebook Twitter Pinterest LinkedIn Tumblr Email Copy Link
Previous ArticleBigBear.ai cuts 2025 revenue outlook to $125M–$140M, leans on record cash as U.S. government AI funding surges
Next Article OpenAI Software Engineer Shares How He Got Hired and Why He Loves It
Advanced AI Editor
  • Website

Related Posts

Wall Street holds near records before the bell Tuesday; IBM jumps on AI partnership with Anthropic

October 7, 2025

IBM Unveils Advancements Across Software and Infrastructure to Help Enterprises Operationalize AI

October 7, 2025

IBM Releases Open-Source Granite 4.0 Generative AI

October 7, 2025

Comments are closed.

Latest Posts

Basquiat Work on Paper Headline’s Phillips’ Frieze Week Sales

Tomb of Amenhotep III Reopens After Two-Decade Renovation    

Limited Edition Print of Ozzy Osbourne Art Sold To Benefit Charities

Odili Donald Odita Sues Jack Shainman Gallery over ‘Withheld’ Artworks

Latest Posts

From Static Products to Dynamic Systems

October 7, 2025

Dual AI engines: LLMs and optimizers sweep September mega-round funding

October 7, 2025

'Western Qwen': IBM wows with Granite 4 LLM launch and hybrid Mamba/Transformer architecture

October 7, 2025

Subscribe to News

Subscribe to our newsletter and never miss our latest news

Subscribe my Newsletter for New Posts & tips Let's stay updated!

Recent Posts

  • From Static Products to Dynamic Systems
  • Dual AI engines: LLMs and optimizers sweep September mega-round funding
  • 'Western Qwen': IBM wows with Granite 4 LLM launch and hybrid Mamba/Transformer architecture
  • OpenAI and the race for AI-driven commerce
  • Intro to Agent Builder

Recent Comments

  1. Geri on Study: AI-Powered Research Prowess Now Outstrips Human Experts, Raising Bioweapon Risks
  2. RonaldCrymn on ‘AI won’t make us lazy, it’ll make us smarter’: Google DeepMind CEO on learning and future of coding | Technology News
  3. Emile Sanderlin on Tech Layoffs Remain Stubbornly High, With Big Tech Leading The Way
  4. Garland Sellen on Steven Pinker: AI in the Age of Reason | Lex Fridman Podcast #3
  5. Kia Loy on Global Venture Capital Transactions Plummet by 32%, Asia Accounts for Less Than 10% in Q1 AI Funding_global_The

Welcome to Advanced AI News—your ultimate destination for the latest advancements, insights, and breakthroughs in artificial intelligence.

At Advanced AI News, we are passionate about keeping you informed on the cutting edge of AI technology, from groundbreaking research to emerging startups, expert insights, and real-world applications. Our mission is to deliver high-quality, up-to-date, and insightful content that empowers AI enthusiasts, professionals, and businesses to stay ahead in this fast-evolving field.

Subscribe to Updates

Subscribe to our newsletter and never miss our latest news

Subscribe my Newsletter for New Posts & tips Let's stay updated!

LinkedIn Instagram YouTube Threads X (Twitter)
  • Home
  • About Us
  • Advertise With Us
  • Contact Us
  • DMCA
  • Privacy Policy
  • Terms & Conditions
© 2025 advancedainews. Designed by advancedainews.

Type above and press Enter to search. Press Esc to cancel.