Who’s Betting, Where, and Why in AI – SwissCognitive AI Investment Radar

As global AI funding levels remain elevated, this week’s investment activity reveals a tightening pattern: fewer hubs, bigger bets, and sharper focus. Silicon Valley, Beijing, and Paris now account for 80% of global AI funding, while other regions navigate capital scarcity and look for niche leverage. Meanwhile, Amazon’s CEO used his annual letter to justify billions already spent, calling AI investments a necessity for long-term competitiveness.

In San Francisco, startup Virtue AI secured $30 million to tackle deployment risk, a concern that’s becoming more pronounced as adoption scales. UK-based Synthesia reported $100 million in revenue and welcomed Adobe Ventures as a new backer, underscoring the value of enterprise AI tools that are already delivering results. And in China, a newly launched $8 billion AI fund backed by government and finance ministries will channel early-stage investments into foundational research and startup formation.

CEE continues to gain investor attention as a cost-efficient and increasingly capable AI development region, while Korea saw a domestic political pledge of $70 billion toward AI initiatives. On the infrastructure front, Nvidia’s $500 billion long-term strategy—including chips and supercomputing partnerships—continues to drive share price gains, while nEye Systems closed a $58 million round to push optical chip development further into the AI stack.

Big tech players aren’t staying out of the startup scene either. Alphabet and Nvidia reportedly invested in SSI, the new venture by OpenAI co-founder Ilya Sutskever, and ex-OpenAI CTO Mira Murati’s startup is reportedly eyeing a massive $2 billion seed round. CMA CGM’s €100 million partnership with Mistral AI brings logistics into the funding spotlight, and the trend toward agentic AI for financial research continues to spread across fintech.

Previous SwissCognitive AI Radar: AI Funding Highlights.

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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EU and France Go Big on AI – SwissCognitive AI Investment Radar

The AI investment landscape is taking another major leap forward this week, as governments and private investors pour billions into AI infrastructure and innovation. The European Union announced a massive €200 billion AI investment initiative, including a dedicated fund for AI gigafactories, signaling Europe’s intent to strengthen its global AI position. Meanwhile, French President Emmanuel Macron revealed a €109 billion AI investment package, just ahead of the AI Summit in Paris, where industry leaders like OpenAI’s Sam Altman are expected to weigh in on the future of AI policy and development.

Beyond Europe, AI capital continues to flow across the world. Saudi Arabia secured $14.9 billion in AI investments at the LEAP 25 tech conference, further reinforcing its ambition to become a major AI hub. Additionally, the kingdom has committed $1.5 billion to AI chip firm Groq, boosting its semiconductor and AI infrastructure efforts. Meanwhile, in India, 76% of companies already report positive AI returns, driving a wave of long-term AI investments as businesses look to integrate AI across new applications.

Private sector players are equally active. The Iliad Group announced a $3 billion AI investment, strengthening its position as Europe’s leading AI cloud provider. At the same time, Brookfield is committing €20 billion to AI projects in France, reinforcing the country’s growing reputation as a European AI powerhouse. SoftBank, however, reported a $2.4 billion loss in its Vision Fund but remains focused on long-term AI investments despite short-term financial turbulence.

Amid this investment frenzy, AI-driven sustainability solutions are gaining traction, as companies face mounting regulatory pressures. Clarity AI’s latest platform helps fund managers streamline ESG compliance, while Standard Chartered and the London Stock Exchange Group (LSEG) are deploying AI-powered investment tools to enhance retail investor strategies.

With Europe easing AI regulations to encourage competitiveness and Baidu’s CEO defending aggressive AI investments, the conversation is shifting from investment size to long-term returns and strategic positioning.

Next week’s developments are sure to bring more insights into where capital is flowing and how investors are adapting. Stay tuned!

Previous SwissCognitive AI Radar: AI Market Adjustments and Billion-Dollar Bets.

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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Dalith Steiger-Gablinger, Co-Founder SwissCognitive – “AI Takes Center Stage at Davos 2025: A SwissCognitive Perspective”

As the snow-capped peaks of Davos played host to the World Economic Forum 2025, the air was thick with excitement and a palpable sense of urgency. This year’s theme, “Collaboration for the Intelligent Age,” set the stage for intense discussions on artificial intelligence (AI) and its potential to reshape our world. As co-founders of SwissCognitive, Andy Fitze and I, Dalith Steiger, had the privilege of being flies on the wall at various public side events, soaking in the insights and debates that unfolded.

The buzz around AI was impossible to ignore, with sessions ranging from “Harnessing AI for Social Innovation” to “The Pulse of AI Innovation”. Clearly, the technology has moved beyond mere hype and into the realm of transformative force. As James Ong, one of the panellists, aptly put it, “We need to rethink the philosophy and the relationship between AI and human beings.” AI is not just a tool; it’s a paradigm shift that will redefine how we work, live, and interact with the world around us.”

“We need to rethink the philosophy and the relationship between AI and human beings.” James Ong, Founder and Director of Artificial Intelligence International Institute [AIII]

One of the most striking aspects of the discussions was the emphasis on collaboration. Gone are the days of siloed AI development. The consensus at Davos was clear: to harness the full potential of AI and ensure its benefits are widely distributed, we need unprecedented levels of cooperation between governments, businesses, and civil society.

Another discussion that deeply resonates with our vision at SwissCognitive is the AI discussion in avoiding the pitfalls of the digital divide, emphasising the need for AI to “lift all boats” rather than exacerbate existing inequalities. We strongly advocated for inclusive AI development.

The ethical implications of AI were another hot topic. The sentiment that we are not just building algorithms; we are shaping the future of humanity was echoed across multiple panels, with discussions ranging from AI’s impact on privacy to its potential to either mitigate or exacerbate climate change.

As we navigated the bustling streets of Davos, Andy and I found ourselves in impromptu discussions with fellow attendees. One of the enlightening discussions was while waiting for the Meta hot chocolate or queuing for the entrance of the Dome. One thing that was present through all our exchanges. People engaged openly, with respect and humour.

The energy was infectious, with everyone from startup founders to policymakers eager to share their perspectives on AI’s future. One conversation that stuck with us was with a young entrepreneur who’s using AI to tackle food waste in developing countries. It was a powerful reminder of AI’s potential to address some of our most pressing global challenges and SDGs.

The governance of AI emerged as a critical theme throughout the forum. With the rapid pace of AI development, there’s a growing recognition that our regulatory frameworks need to evolve just as quickly. The call for adaptive, agile governance structures was loud and clear. We shouldn’t govern 21st-century technology with 20th-century laws!

“We shouldn’t govern 21st-century technology with 20th-century laws!” during a Chatham rules debate

Perhaps the most stimulating discussions, however, centred around the potential of AI to complement human capabilities rather than replace them. AI should be seen as a co-pilot, not an autopilot. As advocates of collaboration between humans and AI, Andy and I were heartened to hear leaders from different sectors emphasise the importance of involving humans in development.

“AI should be seen as a co-pilot, not an autopilot.” during a Chatham rules debate

The Open Source Revolution: A Game-Changer in the Global AI Race

Another topic that consistently emerged in our conversations was the growing importance of open source in AI development. This trend is not just reshaping the technological landscape; it’s also challenging the traditional narrative of national AI supremacy.

The United States’ commitment to investing a staggering $500 billion in AI over the next three years is undoubtedly headline-grabbing. However, as Yann LeCun, VP & Chief AI Scientist at Meta, astutely pointed out during several discussions in Davos, the real story might be the rise of open-source models rather than any single nation’s dominance.

LeCun’s perspective is particularly illuminating: “To people who see the performance of DeepSeek and think: ‘China is surpassing the US in AI.’ You are reading this wrong. The correct reading is: ‘Open source models are surpassing proprietary ones.'”

“Open source LLM models are surpassing proprietary ones.” Yann LeCun, VP & Chief AI Scientist at Meta

This shift towards open source is democratising AI development on a global scale. LeCun explained that “DeepSeek has profited from open research and open source (e.g. PyTorch and Llama from Meta). They came up with new ideas and built them on top of other people’s work. Because their work is published and open source, everyone can profit from it. That is the power of open research and open source.”

Indeed, the open-source movement in AI is gaining momentum rapidly. Models like Llama 2, Mistral, and DeepSeek are not just matching but, in some cases, surpassing the capabilities of proprietary giants like GPT-4 and Google Gemini. This trend is reshaping the AI ecosystem, offering adaptability, cost-efficiency, and privacy compliance that many enterprises find increasingly attractive.

The implications of this shift are profound. While national investments like the U.S.’s $500 billion commitment are crucial, the collaborative nature of open-source development means that innovations can come from anywhere. This global pool of talent and ideas could potentially accelerate AI development far beyond what any single nation or company could achieve alone.

Moreover, the open source movement aligns with the growing calls for AI transparency and accountability. One tech executive at Davos noted, “We’re not just building algorithms; we’re shaping the future of humanity.” Open source development allows for greater scrutiny and collective problem-solving, potentially leading to safer and more ethical AI systems.

“We’re not just building algorithms; we’re shaping the future of humanity.” CEO during a Panel in Davos

As we reflect on the discussions at Davos, it’s clear that the future of AI is not just about who can invest the most money. It’s about fostering a global ecosystem of innovation, collaboration, and shared progress. The rise of open source in AI is not just a technological trend; it’s a paradigm shift that could redefine how we approach some of the world’s most pressing challenges.

In this new landscape, the winners will not necessarily be the nations or companies with the deepest pockets but those who can best harness the collective intelligence of the global AI community. As we move forward, it will be fascinating to see how this open-source revolution continues to shape the future of AI and, by extension, our world.

“In this new landscape, the winners will not necessarily be the nations or companies with the deepest pockets, but those who can best harness the collective intelligence of the global AI community.” Andy Fitze, Co-Founder SwissCognitive

As the forum drew to a close, we left Davos with a sense of cautious optimism. The challenges ahead are significant, but so too is the collective will to address them. The conversations made it clear that we are at a pivotal moment in the development of AI, and the decisions we make now will shape its trajectory for years to come. This future belongs to the young generations. We, the older generation, must be aware that every decision we make won’t affect us, as it will affect the younger generations! This responsibility is imperative!

As we return to our work at SwissCognitive, we’re more energised than ever to continue fostering dialogue and collaboration in AI. The insights gained at Davos will undoubtedly inform our efforts to build a future where AI truly lifts all boats, creating a rising tide of innovation and prosperity for all.

“We are the change we wanna see”, Yip Thy Diep Ta, Founder & CEO @ J3D.AI, House of Collaboration

In reflecting on our experience, Andy remarked, “The technical possibilities of AI are astounding, but it’s the human ingenuity in applying these technologies that will truly change the world.” I couldn’t agree more, adding, “AI has the power to amplify our human potential, but only if we approach its development with empathy, wisdom, and a commitment to inclusivity.“

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Who’s Investing and Why in AI – SwissCognitive AI Investment Radar

From ByteDance’s $12 billion AI chip investment in 2025, aiming to strengthen its infrastructure, to Trump’s announcement of up to $500 billion in private sector investments, the focus on AI-driven infrastructure continues to expand across industries and geographies.

The UK’s AI sector has been attracting £200 million per day in private investment, highlighting strong confidence in its long-term growth potential. Meanwhile, China’s newly established $8.2 billion AI investment fund comes as a direct response to tightened US trade controls, signaling a strategic push to build domestic AI capabilities amid geopolitical challenges. On a different note, Capgemini’s research finds that 67% of businesses in Singapore see AI as their top investment priority for 2025.

Private firms are also positioning themselves for growth, with Nvidia set to invest over $500 million in a new AI research facility in Israel, aiming to accelerate advancements in AI technologies. Similarly, DDN’s $300 million funding from Blackstone is positioning the company as a leader in AI storage solutions, building on its established presence in high-performance computing.

However, despite the influx of investments, many companies are grappling with the ROI puzzle of AI, as leaders weigh the balance between potential and profitability. Some businesses are even considering selling non-core assets to fund AI projects, underscoring the financial pressures that come with large-scale adoption.

As AI investments continue to shape the global economy, staying informed about emerging trends and strategic priorities will be critical for stakeholders looking to navigate this rapidly evolving space. Join us next week too!

Previous SwissCognitive AI Radar: AI in Corporate Budgets and National Strategies.

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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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 Guest Blogger: Zachary Amos – “How Countries Are Using AI to Predict Crime”

A world where police departments can predict when, where and how crimes will occur seems like something from a science fiction novel. Thanks to artificial intelligence, it has become a reality. Already, countries are using this technology to forecast misconduct.

How Do AI-Powered Crime Prediction Systems Work?

Unlike regular prediction systems — which typically use hot spots to determine where and when future misconduct will be committed — AI can analyze information in real time. It may even be able to complete supplementary tasks like summarizing a 911 call, assigning a severity level to a crime in progress or using surveillance systems to tell where wanted criminals will be.

A machine learning model evolves as it processes new information. Initially, it might train to find hidden patterns in arrest records, police reports, criminal complaints or 911 calls. It may analyze the perpetrator’s demographic data or factor in the weather. The goal is to identify any common variable that humans are overlooking.

Whether the algorithm monitors surveillance camera footage or pours through arrest records, it compares historical and current data to make forecasts. For example, it may consider a person suspicious if they cover their face and wear baggy clothes on a warm night in a dark neighborhood because previous arrests match that profile.

Countries Are Developing AI Tools to Predict Crime

While these countries don’t currently have official AI prediction tools, various research groups and private police forces are developing solutions.

• United States

Violent and property crimes are huge issues in the United States. For reference, a burglary occurs every 13 seconds — almost five times per minute — causing an average of $2,200 in losses. Various state and local governments are experimenting with AI to minimize events like these.

One such machine learning model developed by data scientists from the University of Chicago uses publicly available information to produce output. It can forecast crime with approximately 90% accuracy up to one week in advance.

While the data came from eight major U.S. cities, it centered around Chicago. Unlike similar tools, this AI model didn’t depict misdemeanors and felonies as hot spots on a flat map. Instead, it considered cities’ complex layouts and social environments, including bus lines, street lights and walkways. It found hidden patterns using these previously overlooked factors.

• South Africa

Human trafficking is a massive problem in South Africa. For a time, one anti-human trafficking non-governmental organization was operating at one of the country’s busiest airports. After the group uncovered widespread corruption, their security clearance was revoked.

At this point, the group needed to lower its costs from $300 per intercept to $50 to align with funding and continue their efforts. Its members believed adopting AI would allow them to do that. With the right data, they could save more victims while keeping costs down.

Some Are Already Using AI Tools to Predict Crime

Governments have much more power, funding and data than nongovernmental organizations or research groups, so their solutions are more comprehensive.

• Japan

Japan has an AI-powered app called Crime Nabi. The tool — created by the startup Singular Perturbations Inc. — is at least 50% more effective than conventional methods. Local governments will use it for preventive patrols.

Once a police officer enters their destination in the app, it provides an efficient route that takes them through high-crime areas nearby. The system can update if they get directed elsewhere by emergency dispatch. By increasing their presence in dangerous neighborhoods, police officers actively discourage wrongdoing. Each patrol’s data is saved to improve future predictions.

Despite using massive amounts of demographic, location, weather and arrest data — which would normally be expensive and incredibly time-consuming — Crime Nabi processes faster than conventional computers at a lower cost.

• Argentina

Argentina’s Ministry of Security recently announced the Artificial Intelligence Applied to Security Unit, which will use a machine learning model to make forecasts. It will analyze historical data, scan social media, deploy facial recognition technology and process surveillance footage.

This AI-powered unit aims to catch wanted persons and identify suspicious activity. It will help streamline prevention and detection to accelerate investigation and prosecution. The Ministry of Security seeks to enable a faster and more precise police response.

• South Korea

A Korean research team from the Electronics and Telecommunications Research Institute developed an AI they call Dejaview. It analyzes closed-circuit television (CCTV) footage in real time and assesses statistics to detect signs of potential offenses.

Dejaview was designed for surveillance — algorithms can process enormous amounts of data extremely quickly, so this is a common use case. Now, its main job is to measure risk factors to forecast illegal activity.

The researchers will work with Korean police forces and local governments to tailor Dejaview for specific use cases or affected areas. It will mainly be integrated into CCTV systems to detect suspicious activity.

Is Using AI to Stop Crime Before It Occurs a Good Idea?

So-called predictive policing has its challenges. Critics like the National Association for the Advancement of Colored People argue it could increase racial biases in law enforcement, disproportionately affecting Black communities.

That said, using AI to uncover hidden patterns in arrest and police response records could reveal bias. Policy-makers could use these insights to address the root cause of systemic prejudice, ensuring fairness in the future.

Either way, there are still significant, unaddressed concerns about privacy. Various activists and human rights organizations say having a government-funded AI scan social media and monitor security cameras infringes on freedom.

What happens if this technology falls into the wrong hands? Will a corrupt leader use it to go after their political rivals or journalists who write unfavorable articles about them? Could a hacker sell petabytes of confidential crime data on the dark web?

Will More Countries Adopt These Predictive Solutions?

More countries will likely soon develop AI-powered prediction tools. The cat is out of the bag, so to speak. Whether they create apps exclusively for police officers or integrate a machine learning model into surveillance systems, this technology is here to stay and will likely continue to evolve.

About the Author:

Zachary Amos is the Features Editor at ReHack, where he writes about artificial intelligence, cybersecurity and other technology-related topics.

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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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Copyright: fastcompany.com – “For Truly Intelligent AI, We Need to Mimic the Brain’s Sensorimotor Principles”

Brains suggest an alternate way to build AI—one that will replace deep learning as the central technology for creating artificial intelligence.

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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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Building AI’s Future – SwissCognitive AI Investment Radar

As major players double down on AI, Coatue Management is leading the charge with a bold $1 billion fund to fuel cutting-edge advancements, while Amazon’s CEO, Andy Jassy, reassures investors that the company’s surging 81% capital expenditures on generative AI will yield returns. Across the globe, China’s DeepRoute.ai secures $100 million to accelerate smart driving technology adoption, signaling rapid growth in autonomous driving.

The Middle East and North Africa (MENA) region also see substantial commitments, with Google dedicating $15 million to boost AI skills, research, and infrastructure through its new AI Opportunity Initiative. Meanwhile, Nvidia and TSMC’s market values surged in October, reflecting the persistent demand for AI chips and the pivotal role of hardware in advancing AI capacities.

As Microsoft pledges an additional $10 billion toward CoreWeave’s GPU infrastructure and Elon Musk courts Middle Eastern investors to raise xAI’s valuation to $45 billion, the global AI landscape is abuzz with momentum. Yet, the wave of Big Tech investments is also testing investor patience as Meta, Amazon, and Microsoft’s hefty AI expenditures begin to weigh on short-term profitability.

Join and explore the critical investments and strategic shifts that define AI’s trajectory, from transformative tech developments to the challenges and promises that lie ahead for investors and innovators alike.

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