From Mega Rounds to Market Ripples – SwissCognitive AI Investment Radar

The AI Investment Radar is back with another Thursday-to-Thursday round-up of the most significant developments in global AI funding and strategic investment. This week, headline attention was dominated by Anthropic’s $3.5 billion round—March’s largest raise—marking a continued race among frontier model developers. Yet beyond that, capital movements spanned from public sector commitments to corporate scaling strategies.

EY-Parthenon announced a $250 million allocation toward AI-powered edge platforms, while Deloitte reaffirmed its $3 billion commitment by expanding its Global Simulation Center of Excellence. OpenAI’s plans for a $40 billion round, led by SoftBank, underscored how large-scale compute and model development remain critical funding priorities.

At a government level, the EU pledged €1.3 billion to develop AI and digital skills under its Digital Europe Programme. On a global scale, IDC projects that AI investments will add $22.3 trillion in economic value by 2030, equating to nearly $5 for every dollar spent. Meanwhile, philanthropic and regional efforts—from Google’s $10 million AI grant to nonprofits, to Mastercard’s investment in Singapore-based AIDA—highlight the growing importance of distributed innovation.

CoreWeave’s downscaled IPO, along with continued investor concerns about AI implementation gaps, also offer a more tempered look at the market’s momentum. Yet from drug discovery at Isomorphic Labs to AI-enabled supply chain optimization, the range and depth of AI deployments continue to grow.

Tune in next week for more updates of the world of AI investments.

Previous SwissCognitive AI Radar: Global AI Capital Moves at Full Speed.

Our article does not offer financial advice and should not be considered a recommendation to engage in any securities or products. Investments carry the risk of decreasing in value, and investors may potentially lose a portion or all of their investment. Past performance should not be relied upon as an indicator of future results.

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$100B for AI Chips, $40B for AI Bets – SwissCognitive AI Investment Radar

AI investment shows no signs of slowing, with capital flowing across semiconductors, cloud AI, financial AI, and responsible AI initiatives. This week, TSMC is preparing a staggering $100 billion investment in U.S. chip production, reinforcing the U.S. AI supply chain. Meanwhile, Anthropic’s valuation tripled to $61.5 billion, after securing $3.5 billion in funding to keep pace with OpenAI and DeepSeek.

The private sector’s AI appetite remains insatiable. Blackstone’s Jonathan Gray emphasized AI’s dominance in global investment trends, while Guggenheim and billionaire investors assembled a $40 billion AI investment pool to fuel finance, sports, and media innovation. Meanwhile, Canva’s AI report revealed that 94% of marketers have now integrated AI into their operations, marking a fundamental shift in business strategy.

The global AI race is also drawing government interest. The European Commission announced a €200 billion mobilization for AI investments, alongside France’s €109 billion push, as President Macron aims to position Europe as a heavyweight in AI development. Across the globe, China’s Honor pledged $10 billion to AI investment, deepening ties with Google for a global expansion.

The infrastructure for AI applications continues to scale rapidly. DoiT announced a $250 million fund dedicated to AI-driven cloud operations, while Shinhan Securities backed Lambda Labs with a $9.3 million investment to advance NVIDIA GPU-powered AI cloud services. Meanwhile, Accenture is doubling down on AI decision intelligence, backing Aaru to improve AI-powered behavioral simulations.

Beyond the corporate sphere, responsible AI investments are gaining traction. Chinese firms are increasing spending on ethical AI as part of a broader strategy to align AI governance with innovation. Meanwhile, Blackstone committed $300 million to AI-driven Insurtech, supporting AI-powered safety solutions in insurance.

With tech giants, startups, and governments all placing massive bets on AI, the sector’s financial landscape is evolving faster than ever. Investors are watching closely as AI’s long-term ROI takes center stage.

How will the capital influx shape AI’s next phase? The coming months will bring more answers.

Previous SwissCognitive AI Radar: AI Expansion and This Week’s Top Investments.

Our article does not offer financial advice and should not be considered a recommendation to engage in any securities or products. Investments carry the risk of decreasing in value, and investors may potentially lose a portion or all of their investment. Past performance should not be relied upon as an indicator of future results.

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SwissCognitive Guest Blogger: Samir Anil Jumade – “The Relentless Tide of Technological Disruption: Are You Ready?”

The world is evolving at an unprecedented pace, driven by rapid technological advancements. Many industries that once seemed invincible have either vanished or are on the verge of collapse due to their failure to adapt. The rise of artificial intelligence (AI), automation, blockchain, and digital platforms is fundamentally reshaping how businesses operate.

In this article, we explore how past giants like Kodak and Nokia disappeared, how today’s industries are facing a similar existential crisis, and how individuals and businesses must prepare for this inevitable transformation.

The Rise and Fall of Industry Giants

Remember Kodak? In 1997, they employed 160,000 people and dominated the photography market, with their cameras capturing 85% of the world’s images. Fast forward a few years, and the rise of mobile phone cameras decimated Kodak, leading to bankruptcy and the loss of all those jobs. Kodak’s story isn’t unique. A host of once-dominant companies, like HMT, Bajaj, Dyanora, Murphy, Nokia, Rajdoot, and Ambassador, failed to adapt and were swept aside by the relentless tide of technological change. These weren’t inferior products; they simply couldn’t evolve with the times.

This isn’t just a nostalgic look back. It’s a stark warning. The world is changing faster than ever, and we’re on the cusp of another massive transformation – the Fourth Industrial Revolution. Think about how much has changed in the last decade. Now imagine the next ten years. Experts predict that 70-90% of today’s jobs will be obsolete within that time frame. Are we prepared?

Look at some of today’s giants. Uber, the world’s largest taxi company, owns no cars. Airbnb, the biggest hotel chain, owns no hotels. These companies, built on software and connectivity, are disrupting traditional industries and redefining how we live and work. This disruption is happening across all sectors.

Consider the legal profession. AI-powered legal software like IBM Watson can analyze cases and provide advice far more efficiently than human lawyers. Similarly, in healthcare, diagnostic tools can detect diseases like cancer with greater accuracy than human doctors. These advancements, while offering immense potential benefits, also threaten to displace a significant portion of the workforce.

The automotive industry is another prime example. Self-driving cars are no longer science fiction; they’re a rapidly approaching reality. Imagine a world where 90% of today’s cars are gone, replaced by autonomous electric or hybrid vehicles. Roads would be less congested, accidents drastically reduced, and the need for parking and traffic enforcement would dwindle. But what happens to the millions of people whose livelihoods depend on driving, car insurance, or related industries?

Even the way we handle money is transforming. Cash is becoming a relic of the past, replaced by “plastic money” and, increasingly, mobile wallets like Paytm. This shift towards digital transactions offers convenience and efficiency, but also raises questions about security, privacy, and the future of traditional banking.

From STD Booths to Smartphones: A Revolution in Communication

Think back to the time when STD booths lined our streets. These public call offices were once essential for long-distance communication. But the advent of mobile phones sparked a revolution that swept STD booths into obsolescence. Those who adapted transformed into mobile recharge shops, only to be disrupted again by the rise of online mobile recharging. Today, mobile phone sales are increasingly happening directly through e-commerce platforms like Amazon and Flipkart, further highlighting the rapid pace of change.

The Evolving Definition of Money

The concept of money itself is undergoing a radical transformation. We’ve moved from cash to credit cards, and now mobile wallets are gaining traction. This shift offers convenience and efficiency, but it also has broader implications. As we move towards a cashless society, we need to consider the potential impact on financial inclusion, security, and privacy.

The Message is Clear: Adapt or Be Left Behind

The message is clear: adaptation is no longer a choice; it’s a necessity. We must embrace lifelong learning and upskilling to navigate this rapidly changing landscape. We need to foster creativity, critical thinking, and problem-solving skills – qualities that are difficult for machines to replicate. The future belongs to those who can innovate, adapt, and thrive in a world increasingly shaped by technology. The question is: will you be ready?

Additional Points to Consider:

· The environmental impact of technological advancements, both positive and negative.

· The ethical considerations surrounding AI and automation.

· The role of government and education in preparing the workforce for the future.

· The potential for new industries and job roles to emerge. By staying informed and proactive, we can harness the power of technology to create a better future for all.

References:

1. D. Deming, P. Ong, and L. H. Summers, “Technological Disruption in the Labor Market,” National Bureau of Economic Research, Working Paper No. 33323, Jan. 2025.
2. K. Hötte, M. Somers, and A. Theodorakopoulos, “Technology and Jobs: A Systematic Literature Review,” arXiv preprint arXiv:2204.01296, Apr. 2022.
3. D. Acemoglu and P. Restrepo, “Assessing the Impact of Technological Change on Similar Occupations,” Proceedings of the National Academy of Sciences, vol. 119, no. 40, e2200539119, Oct. 2022.
4. D. Acemoglu and P. Restrepo, “Occupational Choice in the Face of Technological Disruption,” National Bureau of Economic Research, Working Paper No. 29407, Oct. 2021. 5.S. Y. Lu and R. Zhao, “Artificial Intelligence for Data Classification and Protection in Cross-Border Transfers,” IEEE Transactions on Big Data, vol. 7, no. 3, pp. 536-545, 2021.

About the Author:

Samir Jumade is a passionate and experienced Blockchain Engineer with over three years of expertise in Ethereum and Bitcoin ecosystems. As a Senior Blockchain Engineer at Woxsen University, he has led innovative projects, including the Woxsen Stock Exchange and Chain Reviews, leveraging smart contracts, full nodes, and decentralized applications. With a strong background in Solidity, Web3.js, and backend technologies, Samir specializes in optimizing transaction processing, multisig wallets, and blockchain architecture.

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SwissCognitive Guest Blogger: Dileep Kumar Pandiya – “AI for Transformative Enterprise Growth: Insights from a Principal Engineer”

You know, it’s amazing to think about. Imagine your sales team closing deals twice as fast. Or your supply chain just adapting on the spot when the market shifts. Honestly, it’s not something from the future—it’s happening now, all thanks to AI.

I have been working in tech for almost 18 years, and I’ve seen how these tools turn ambitious ideas into actual results. I want to show you what that looks like in real life—where AI didn’t just help businesses grow, it completely changed the game.

How AI Unlocks Growth in Enterprises

What if your business could predict customer needs before they even knew them? AI makes this possible. It’s no longer about guesswork or reacting late; it’s about proactive strategies powered by data.
Take a retail chain struggling with overstock issues. By implementing AI to forecast demand using real-time trends, they reduced inventory waste by 20% and increased availability of high-demand items by 15%. It’s a transformation that goes beyond efficiency—it’s about building smarter, more agile businesses.

AI Copilot: Redefining Sales with AI

Sales has always been about timing and relationships. But what if AI could help you focus on the right opportunities at exactly the right moment? That’s the promise of AI Copilot.
When we launched Copilot, the goal was simple: empower sales teams to act smarter and faster. By integrating AI, I built a platform that could analyze millions of data points in seconds to identify high-potential accounts. The result: Sales teams were no longer overwhelmed by data they were driven by insights.
Here’s what stood out most to me: within three months, Copilot wasn’t just saving time—it was generating millions in additional revenue. Seeing the tangible impact on businesses and hearing feedback like “I can’t imagine working without this” made every late night worth it.

Scaling Smarter with AI and Microservices

Think of a system that can process thousands of real-time events every second, with no downtime. That’s what we built with the Phoenix Project, a scalable platform that uses AI and microservices to empower B2B clients.
One client used this platform to optimize marketing campaigns dynamically. Instead of waiting weeks for data analysis, they could adjust strategies on the fly, improving lead quality by 30% and cutting acquisition costs dramatically. It’s proof that scalability isn’t just a technical goal—it’s a business imperative.

Lessons for Enterprises Ready to Embrace AI

Here’s a story I often share: A small business hesitant to invest in AI started with a single pilot project—automating customer inquiries with AI chatbots. Within six months, they expanded the system to handle order tracking, inventory checks, and even personalized product recommendations. Today, they credit AI for a 25% increase in customer retention.
My takeaway is to start small, but think big. AI’s value compounds over time, so even small steps can lead to significant transformations.

Future Trends in AI and Enterprise Growth

The future isn’t just about doing things faster—it’s about doing them smarter. Imagine systems that can explain their decisions clearly or tools that work alongside humans to tackle complex problems.
One trend I’m particularly excited about is real-time decision-making. For example, picture a global logistics company rerouting shipments during a storm, avoiding delays and cutting costs. This kind of agility is becoming the new standard, and businesses that embrace it early will set themselves apart.

Final Thoughts

AI is the foundation for building the future of business. Whether it’s transforming sales strategies, driving efficiency, or enabling agility, the opportunities are immense. My advice: Don’t wait for the perfect moment to start. Take a step, learn, and grow with AI.

About the Author:

Dileep Kumar Pandiya is a globally recognized Principal Engineer with over 18 years of groundbreaking work in AI and enterprise technology. He has pioneered transformative AI-driven platforms and scalable systems, driving innovation for Fortune 500 companies like ZoomInfo, Walmart, and IBM. His leadership has redefined sales technology and digital transformation, earning him prestigious awards and international acclaim for his contributions to business growth and industry advancement. Known for his ability to blend visionary thinking with practical solutions, Dileep continues to shape the future of enterprise technology.

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Copyright: forbes.com – “Emotional Intelligence is More Important Than Ever in the Age of AI”

While most of us accept that artificial intelligence isn’t going to take over the world just yet, there’s a growing recognition that businesses and their employees are going to have to adapt their skills pretty swiftly. According to the 2024 Global CEO Survey from consulting firm PwC, seven out of 10 CEOs believe that AI will significantly change the way their company creates, delivers and captures value over the next three years. On the plus side, 41% believe it will increase revenue. However, those in “AI-exposed” jobs (such as administration and customer service agents) have seen 27% lower job growth, and anticipate a 25% higher skills change rate than those who are not at risk.

In most cases, AI won’t replace entire jobs, but speed up or automate certain aspects of them, often freeing staff up to work on something more satisfying or of higher value. The emotionally intelligent, human side of work is something it is unlikely to be able to replicate, at least in the near future. AI’s power lies in being able to process vast amounts of data with speed and accuracy, but its limitations become apparent when it encounters the complexity of human behaviors. It’s also known for its fallibilities, sometimes producing false responses to prompts or biased outcomes because of the data it’s working on or the way it has been programmed.

I define emotional intelligence as self-awareness, which is a critical skill in this increasingly AI-driven world. Whatever level someone is working at, it’s important that they know how to read the room and adapt how they work with a colleague or client.[…]

Read more: www.forbes.com

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SwissCognitive Team and Kilian Woods – “From Ethics to Efficiency: Successfully Scaling AI Across Industries” AI Trajectory 2025: AI Navigator Insights Virtual Conference Wrap-Up

Balancing rapid AI innovation with robust governance and human-centric approaches is essential for responsible development. Scaling AI effectively requires aligning it with ethical standards, sustainability goals, and transparent practices to build trust. AI’s transformative potential lies in improving efficiency, enhancing decision-making, and driving collaboration across industries like healthcare, tourism, and business, while education and upskilling remain critical for its adoption and impact.

Yesterday, the “AI Trajectory 2025: AI Navigator Insights” conference brought together global leaders and innovators to explore the transformative power of AI across industries. This dynamic event featured thought-provoking interviews, insightful panel discussions, and award-winning AI use cases, highlighting the critical balance between innovation, governance, and collaboration in shaping the future of AI.

From leveraging AI for practical integration and scaling innovation responsibly to rethinking competitive advantages in the age of generative AI, the event offered valuable takeaways for organizations and leaders worldwide. Let’s recap the key highlights:

Advancing AI Innovation with Safety at the Core

With Michael Wade

Michael Wade underscored the need to balance rapid AI development with robust governance and cross-border guidelines, emphasizing AI’s dual nature as both a transformative tool and a potential risk.

Michael Wade, Tonomus Professor of Strategy and Digital, IMD and Dalith Steiger, Co-Founder of SwissCognitive

The Five Truths for AI Practical Integration

With Markus Danhel, Amanda Obidike, Johan Steyn, James Ong, Jarrod Anderson

The panel explored strategies for scaling AI cost-effectively while balancing technology, governance, and ethics. Speakers highlighted the importance of trust-building through privacy prioritization and bias audits, integrating human empathy in decision-making, and encouraging education at all organizational levels to foster ethical AI.

Markus Danhel, Head Data & AI, IBM Switzerland, Amanda Obidike, CEO of STEMi Makers of Africa, Johan Steyn, Founder, AI & Automation Thought Leader, AI for Business, James Ong, Founder & Managing Director, Artificial Intelligence International Institute (AIII), Jarrod Anderson, Chief Artificial Intelligence Officer, SYRV.AI

Trusted Value Through GenAI in Swiss Tourism

With Michael Wegmüller and Christian Dernbach

Michael Wegmüller and Dr. Christian Dernbach showcased how generative AI transforms tourism, enhancing efficiency for managers and improving traveler engagement through data-driven insights.

Embracing Collaboration and Co-Innovation

Valeria Sadovykh, Aleksandra Przegalinska, Anita Puppe, Jeannette Gorzala, Bret Greenstein

The speakers delved into the power of partnerships in advancing AI. Discussions ranged from human-centric AI models and regional collaboration to the importance of educating the workforce to adopt and innovate responsibly.

Valeria Sadovykh, Technology Strategist, Microsoft, Aleksandra Przegalinska, Associate Professor and Vice Rector for Innovations and AI, Kozminski University, Harvard University, Anita Puppe, Senior Consultant Strategy & Business Design, IBM iX DACH, Jeannette Gorzala, CEO & Founder, Act.AI.Now, Bret Greenstein, PwC US Partner, Generative AI Leader

Rethinking Competitive Advantage in the Age of GenAI

With José Pedro Almeida

José Pedro Almeida envisioned a future with AI agents revolutionizing healthcare, advising doctors, and transforming business operations for increased efficiency and personalization.

José Pedro Almeida, Chief AI Strategist, World’s Top 70 Health AI

Investing in AI-Driven Innovation

With Jacques Ludik, Ingrid Vasiliu-Feltes, Dr. Maria Fay, Andreas Welsch, Alberto-Giovanni

The AI experts emphasized the importance of aligning AI investments with sustainability, value creation, and regulatory compliance. The panel also explored Agentic AI’s role in personalization and called for transparency and trust-building to unlock AI’s full potential.

Jacques Ludik, Founder & CEO, Cortex Logic & Cortex Group, Founder & President, Machine Intelligence Institute of Africa, Ingrid Vasiliu-Feltes, Founder & CEO Institute for Science, Entrepreneurship and Investments, Deep Tech Diplomacy & Digital Strategist, Dr. Maria Fay, AI Lead, SAP Switzerland, Andreas Welsch, Founder & Chief AI Strategist, Intelligence Briefing, Alberto-Giovanni, Chief AI Officer, HealthAI

Scaling Applied AI for Long-Term Growth

With Behshad Behzadi

Behshad Behzadi provided insights on leveraging AI for broader, more impactful transformations, addressing challenges like governance, scalability, and learning from cross-industry innovations.

Behshad Behzadi, CTO and Chief AI Officer, Sportradar

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Breaking Barriers to AI Funding – SwissCognitive AI Investment Radar

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Copyright: cio.com – “Agentic AI: 6 promising use cases for business”

AI agents will play a vital role in software programming and cybersecurity, but they will also change enterprise workflows and business intelligence, experts say.

Agentic AI is having a moment, as proponents see the benefits of using autonomous AI agents to automate manual tasks across organizations.

Agentic AI, which Forrester named a top emerging technology for 2025 in June, takes generative AI a step further by emphasizing operational decision-making rather than content generation. The promise the approach has for impacting business workflows has organizations such as Aflac, Atlantic Health System, Legendary Entertainment, and NASA’s Jet Propulsion Laboratory already pursuing the technology.

CRM leader Salesforce has since centered its strategy around agentic AI, with the announcement of Agentforce. IT service management giant ServiceNow has also added AI agents to its Now Platform. Microsoft and others are also joining the fray.

With AI agents popping up in so many situations and platforms, organizations interested in the technology may find it difficult to know where to start. A handful of use cases have so far risen to the top, according to AI experts.

Agentic AI will integrate smoothly with ERP, CRM, and business intelligence systems to automate workflows, manage data analysis, and generate valuable reports, says Rodrigo Madanes, global innovation AI officer at EY, a consulting and tax services provider. AI agents, unlike some past automation technologies, can make decisions in real-time, making process automation a primary use case.

“AI agents can automate repetitive tasks that previously required human intervention, such as customer service, supply chain management, and IT operations,” Madanes says. “What sets the technology apart is its ability to adapt to changing conditions and handle unexpected inputs without manual oversight.”[…]

Read more: www.cio.com

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Copyright: sloanreview.mit.edu – “Learning to Manage Uncertainty, With AI”

The second Artificial Intelligence and Business Strategy report of 2024, from MIT Sloan Management Review and Boston Consulting Group, looks at how organizations that combine organizational learning and AI learning are better prepared to manage uncertainty. It examines how the emergence of generative AI is changing workers’ and organizations’ attitude toward the technology and the opportunities and risks that it poses.

Uncertainty Abounds

Uncertainty is all about the unknown. The less an organization knows, the greater its uncertainty and the less able it is to manage resources effectively. Managing uncertainty, therefore, requires learning. Companies need to learn more, and more quickly, to manage uncertainty.

Addressing uncertainty constitutes a pressing challenge for leadership, especially today, when geopolitical tensions, fast-moving consumer preferences, talent disruptions, shifting regulations, and rapidly evolving technologies complicate the business environment. Companies need better tools and perspectives for learning to manage uncertainty arising from these and other business disruptions. Our research finds that a major source of uncertainty, artificial intelligence, is also critical to meeting this challenge. Specifically:

Companies that boost their learning capabilities with AI are significantly better equipped to handle uncertainty from technological, regulatory, and talent-related disruptions compared with companies that have limited learning capabilities.

The Estée Lauder Companies (ELC) offers a case in point. The cosmetics company has a strategic need to anticipate consumer trends ahead of its competitors. In earlier times, consumer preferences might have shifted seasonally. Now, preferences are less certain; shifts happen more quickly due to social media and digital influencers. Fashion trends can change by the week. If the color peach suddenly captures the public’s interest, the company needs to discern that trend as quickly as possible.[…]

Read more: www.sloanreview.mit.edu

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Copyright: cio.com – “AI-Native Software Engineering May Be Closer Than Developers Think”

Over the next three years, many organizations will use AI agents to write the majority of their software, moving developers into review roles, Gartner predicts. But challenges and questions remain.

Developers unimpressed by the early returns of generative AI for coding take note: Software development is headed toward a new era, when most code will be written by AI agents and reviewed by experienced developers, Gartner predicts.

Organizations and vendors are already rolling out AI coding agents that enable developers to fully automate or offload many tasks, with more pilot programs and proofs-of-concept likely to be launched in 2025, says Philip Walsh, senior principal analyst in Gartner’s software engineering practice.

By 2026, “there will start to be more productive, mainstream levels of adoption, where people have kind of figured out the strengths and weaknesses and the use cases where they can go more to an autonomous AI agent,” he says. “In the 2027 range, we’ll really see this paradigm take root, and engineers’ workflows and skill sets will have to really evolve and adapt.

In a recent press release, Gartner predicted that 80% of software engineers will have to reskill to fit into new roles created when generative AI takes over more programming functions.

These AI coding agents will be more advanced than the AI coding assistants in wide use today, but they will still need experienced programmers to check their work and tweak the code, Walsh says. In coming to software development, agentic AI — a rising trend that emphasizes autonomous decision-making over simple content generation — will push the boundaries of current AI coding copilots to enable AI-native software engineering to emerge.

While current AI coding assistants can write snippets of code, they often struggle to create software from scratch, but that won’t be the case for evolving coding agents, Walsh says.[…]

Read more: www.cio.com

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