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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AI took centre stage at Davos 2025, sparking critical conversations on ethics, collaboration, and innovation.

Explore our co-founder Dalith Steiger-Gablinger’s key takeaways and also discover how AI has driven major shifts worldwide through last week.

AI-powered song unites women across 195 countries for equality
Google invests $1B in AI startup Anthropic to push innovation
Pope warns AI could deepen the global ‘crisis of truth
Algorithms offer new solutions to pressing societal challenges
…and more!

Thank you for joining us on this journey. More AI updates are coming soon!

Kind regards,

The Team of SwissCognitive

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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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By Martina Fuchs

Credits: The Female Quotient / The Frequency School – “First Song Ever to Unite Women from All Countries Using Sound Healing Frequencies”

The Frequency School – in partnership with The Female Quotient – launched “195”, the first song in history featuring women from all of the world’s 195 countries using sound healing frequencies and the 528 Hz ‘Love Frequency’ in a bid to ignite a global movement and raise awareness about gender equality across various industries including technology.

The Frequency School co-founded by Grammy-nominated and multi-platinum music producer Maejor, Kingsley Maduka, Brandon Lee, Aaron Dawson and Martina Fuchs premiered this visionary, powerful and universal campaign at a side-event in Davos, Switzerland which took place during the first day of the 55th Annual Meeting of the World Economic Forum (WEF).

Using the sounds of birds and the heartbeat as instrumental elements, “195” aims to raise the world’s frequency, elevate humanity, and trigger a positive impact by uniting and empowering women worldwide.

One woman in every one of the world’s 195 countries recognized by the United Nations said one word: “EQUALITY” in her national language or native tongue.

Martina Fuchs, business journalist and executive producer of the 195 women song, said:

“It has always been my dream to produce the first song in history featuring every country on the planet. Our vision was to unite 195 women from all walks of life from around the globe in this pioneering and groundbreaking initiative to advocate for gender equality and the rights of women and girls, and to help people struggling with mental health issues. Gender equality is not only a fundamental human right, but a necessary foundation for a peaceful, prosperous and sustainable world.”

U.S. Grammy-nominated and multi-platinum music producer Maejor who produced the song using sound healing frequencies said:

“We chose to use 528 Hz for the track which is often referred to as the ‘love frequency’, or the frequency of transformation and miracles. It provides a powerful energetic foundation for creating an environment where equality can flourish. By resonating with a frequency linked to unconditional love, we wanted to promote more respect and fairness for women, as well as deep inner healing and a state of peace. The transformative vibration of 528 Hz can inspire positive action and empathy and people to act more kindly and inclusively.”

According to scientific studies and music theory, Solfeggio frequencies, ranging from 174 Hz to 963 Hz, offer unique sound patterns that promote relaxation, stress relief, and overall well-being. These frequencies have been shown to positively impact mental, emotional, and physical health by generating vibrations that help achieve a state of calm and balance of the mind, body and spirit.

Miriam Moriati, President of the Kiribati Rotaract Youth Club and a Women and Youth representative for OARS (Ocean Alliance for Resilience and Sustainability), said:

“I’m from Kiribati, a small island nation in the Pacific, where our highest point is just 3 meters above sea level. Our women in Kiribati are vulnerable due to gender equality not being part of our culture and traditions. They are often the first to be affected by crises and the last to recover. Being part of this initiative to support women on an international stage is an incredible honor. Opportunities to represent our small country are rare, and I am grateful for this platform to amplify the voices of Kiribati women.”

Dalith Steiger, Co-Founder of SwissCognitive and the voice of Israel in the song said:

“Equality is not just an ideal—it’s our collective responsibility. The lack of gender equality still remains a huge challenge in the technology space that we need to tackle. I’m convinced that AI can support us to unbias the bias! I am grateful to be part of this global women empowerment initiative to raise awareness across various sectors.”

A new white paper by IMD in collaboration with Microsoft Switzerland and EqualVoice released at the WEF on Thursdy provides in-depth analysis and guidance for organizations to mitigate against risks and use AI responsibly.

More than 80% of the world’s organizations are expected to be using GenAI tools in production environments by 2026, and the productivity gains will likely boost global GDP by $7tn in the next decade. Yet even as innovation races ahead, important questions need to be asked about the potential risks.

Read the full report “Mind the Gap Addressing the risk of bias in Generative AI”.

The “195” song is planned to be submitted for a Guinness World Records for the title: “Most nationalities to contribute vocals to a musical recording (single song)”.

@Brandon Lee Shelley Zalis The Female Quotient The Frequency School

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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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SwissCognitive Guest Blogger: Utpal Chakraborty, Chief Digital Officer, Allied Digital Services Ltd., AI & Quantum Scientist – “AI Pioneers Claim Nobel Prizes: Transforming the Future of Science”

The year 2024 will be remembered for generations, marking a historic milestone as artificial intelligence researchers make unprecedented strides in multiple Nobel Prize categories. For the first time, AI pioneers were recognized not solely for advancements in AI itself but for groundbreaking contributions to physics and chemistry. This achievement highlights how the lines between traditional sciences and computer science (specifically AI) are blurring in ways that would have seemed unimaginable just a few decades ago.

The announcement sent ripples through the scientific community when Geoffrey Hinton and John Hopfield shared the Nobel Prize in Physics, while Demis Hassabis along with two other scientists claimed the Chemistry prize. Three brilliant minds known primarily for their AI work, now recognized for transforming our understanding of the physical world.

Geoffrey Hinton and John Hopfield received the Physics Nobel for their work on understanding phase transitions in complex systems through the lens of Neural Computation. Their groundbreaking discovery showed how the mathematics of phase transitions in materials shares fundamental principles with how Neural Networks learn and process information.

Hopfield’s contribution stemmed from his revolutionary 1982 paper (Neural networks and physical systems with emergent collective computational abilities) introducing the Hopfield network, a mathematical model that showed how collections of simple units could exhibit complex behavior similar to phase transitions in physics. The model demonstrated how memory could emerge from the collective behavior of simple components, much like how magnetic properties emerge in materials.

Hinton’s work complemented this by revealing how the principles of statistical mechanics, traditionally used to understand particle behavior in physics, could explain deep learning’s success. His breakthrough came from showing that the way neural networks optimize their weights (Backpropagation) follows the same mathematical principles that govern how physical systems find their lowest energy states.

Of course, many of us know these scientists primarily for their AI contributions:

– Hopfield’s neural networks revolutionized our understanding of associative memory and laid the groundwork for modern deep learning.

– Hinton’s work on backpropagation and deep belief networks essentially created the deep learning revolution we’re experiencing today.

But it’s their ability to bridge these seemingly disparate fields that makes their Physics Nobel Prize so significant. As Hinton once said at a conference, “The brain is a physical system. Why shouldn’t its principles help us understand other physical systems?”

On the other hand, Demis Hassabis’s Chemistry Nobel came for something equally remarkable – using AI principles to solve one of chemistry’s grand challenges, protein folding. His work at DeepMind led to AlphaFold2, but the Nobel recognized his deeper insights into how the principles of reinforcement learning could reveal fundamental rules governing molecular interactions.

The prize specifically acknowledged his team’s discovery of new chemical principles through AI analysis, principles that classical scientists had missed. By training AI systems to understand molecular behavior, they uncovered previously unknown patterns in how proteins fold and interact, revolutionizing our understanding of chemical processes at the molecular level.

Most know Hassabis as the founder of DeepMind and the mind behind AlphaGo, but his journey from AI to chemistry illustrates a broader trend in science. His background in neuroscience and computer games gave him a unique perspective on how complex systems organize themselves, whether they are neural networks, game strategies, or molecular structures.

What makes these Nobel Prizes so fascinating is how they highlight the convergence of different scientific disciplines.

The work of Hinton, Hopfield, and Hassabis shows us that these aren’t separate fields anymore, they are different lenses for viewing the same reality. Their discoveries reveal a deeper unity in science that we are only beginning to appreciate.

As I write this article, I can’t help but feel we are living through a new scientific revolution. The tools of AI aren’t just helping us do traditional science faster; they are fundamentally changing how we think about science itself.

Young researchers today don’t see themselves as just physicists, chemists, or computer scientists. They are explorers in a unified landscape where:

– Physical laws inform neural network design.

– Chemical principles inspire new computing architectures.

– AI algorithms reveal new patterns in nature.

What strikes me most about these Nobel laureates is their humanity. Despite working with machines and mathematical abstractions, they never lost sight of the human element in science.

As someone who has worked in these intersecting fields, I see these Nobel Prizes as more than just recognition of brilliant work. They are a signal that the future of science lies not in specialization, but in synthesis. The next generation of scientists won’t just cross boundaries – they’ll erase them.

These Nobel Prizes aren’t just awards; they are a glimpse of science’s future. A future where the boundaries between classical physics, quantum physics, chemistry, and computation disappear and where artificial intelligence helps us see the unity that was always there.

Der Beitrag AI Pioneers Claim Nobel Prizes: Transforming the Future of Science erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

Copyright: cio.com – “Is Now the Right Time to Invest in Implementing Agentic AI?”

While vendors say their current agentic AI-based offerings are easy to implement, analysts say that’s far from the truth.

Software vendors’ pitches are evolving, with  agentic AI beginning to supplant generative AI in their marketing messages. Rather than just generating code or content for human review agentic AI will, they say, follow instructions, make decisions, and take actions much as a human worker would, without human intervention.

It’s more than just a smarter RPA

Agentic AI isn’t just a better version of robotic process automation (RPA): It promises to take enterprises places RPA never could.

“Think of RPA as a train on tracks — it can only go where the tracks are laid. Agentic AI is more like a self-driving car — it can navigate different routes and situations adaptively,” said Paul Chada, co-founder of agentic AI-based software providing startup Doozer AI.

What makes agentic AI autonomous or able to take actions independently is its ability to interpret data, predict outcomes, and make decisions, learning from new data — unlike traditional RPA, which falters when encountering unexpected data, said Cameron Marsh, senior analyst at Nucleus research.

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Copyright: intelligencebriefing.substack.com – “The Unexpected Role of Data to Unlock Generative AI Value”

On August 20, Quentin Reul (Founder & Chief AI Officer) joined me on “What’s the BUZZ?” and shared the four Generative AI challenges you can’t ignore. Generative AI is reshaping how businesses operate, but not every problem requires a Generative AI solution. In many cases, data is still a critical factor in project success and selecting the right capabilities to explore and implement needs for strategic decision-making. But where should you start? Here is what we’ve talked about…

Generative AI: Not a One-Size-Fits-All Solution

Generative AI thrives in scenarios where creativity is valued and the cost of being wrong is low. However, businesses must proceed cautiously when the stakes are high—such as in legal or medical fields where errors can have severe consequences. Understanding the limitations and strengths of Generative AI is crucial. A technology leader must guide their company in making informed decisions about when and where to use these advanced tools, ensuring that the chosen solution aligns with the business’s core objectives and delivers real value.[…]

Read more: www.intelligencebriefing.substack.com

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SwissCognitive Guest Blogger: Muhammad Irfan – “AI in Investment: How AI is Transforming the World of Financial Portfolios”

Key Takaways:

– Analyze past and current data to give a clearer picture of portfolio risks for better management.
– Integrating AI provides insights that help investment managers make data-driven decisions and maximize returns.
– Helps in portfolio management by automatically deciding how to distribute assets, rebalancing, and managing risks.
– Personalized investment strategies are just a click away with AI.
– Offer insights into market behavior to capitalize on investment opportunities.

Artificial intelligence (AI) has been making tides in every sector—be it finance or healthcare. The use of AI in finance has caught the eye of all stakeholders. According to Statista, the market size of AI in fintech is $44.08 billion in 2024, which is expected to exceed $50 billion in 2029.

At this point, you might be asking yourself what significant changes AI brings to finance. The short answer is that it improves efficiency, supports informed investment decisions, maximizes returns, and more. The long answer? Well, for that, you have to stick around till the end.

AI has completely changed the way investment professionals operate. It automates various administrative tasks and helps to make well-informed investment decisions by analyzing vast amounts of data. In today’s article, we will be understanding the role of AI in investment, financial portfolio management, and making smart decisions.

The Impact of AI on Finance: AI in Investments

AI isn’t just a catchy term. It offers numerous benefits to the finance industry, especially in smart investment, risk assessment, and portfolio management. It aids investment professionals in decision-making by analyzing huge amounts of data.

We all know that it’s highly possible for humans to overlook investment opportunities, but AI systems? Not a chance. Moreover, AI helps in portfolio management by optimizing asset allocations based on market conditions and investor preferences. Enough of the basics; let’s explore the benefits of AI for smart investments in-depth without wasting more time:

Understand Marketing Trends

Will you invest without having any knowledge about the market? Will you be relying on your gut feeling? Surely not. AI plays a pivotal role here and provides investors with insights by analyzing huge amounts of market data.

Utilizing these insights, investors can identify risks and opportunities for investment. It helps professionals make proactive decisions and maximize returns. So when you have a technology like AI, why make guesses? Investors should rely on AI for profitable investment strategies as it is the way forward.

Supports Risk Management

Talking about AI’s role in investment management and not mentioning risk assessment and management is nothing less than a crime. Investment isn’t kid’s play; even the most experienced among us face risks. Manual risk assessment and management is a tedious and time-consuming process that is prone to errors. However, that’s not the case when AI is involved.

AI technology helps to identify potential risks in financial portfolios and provides invaluable recommendations to mitigate them. Curious to know how things work?

AI analyzes large amounts of market data and takes multiple scenarios into consideration to provide an accurate assessment of risks like fraud or market decline and their impact on investment portfolios. This way, investment managers can optimize portfolio performance and achieve their investment goals.

Provide Personalized Investment Advice

Imagine having a companion who knows your risk tolerance and goals and provides personalized advice that leads towards your set goals. Isn’t it great? What if I say you have such a companion but aren’t aware of his capabilities? Yes, you heard it right.

Any guesses as to who it could be? Have you guessed AI? Spot on! AI capabilities extend to wealth management, tailoring investment plans to individual preferences and financial goals. AI helps manage wealth by customizing investment plans to fit personal preferences and financial goals.

Improve Portfolio Management

Another benefit of AI in investment is that it helps with portfolio management. It enables investors to easily automate and improve how they allocate and adjust their assets with the changing market. Name a thing that AI can’t do. Bet you won’t find any!

These modern AI systems evaluate market trends, investor profiles, and economic signs to optimize portfolios so they match individual goals and risk levels. What’s more, investors can predict asset performance using AI, which helps in proactive adjustments.

Factors to Weigh When Using AI in Investment Decision-Making

Bias & Fairness

We all know that AI systems are trained on data. It means any biases in data can lead to discrimination or undesired outcomes. To avoid such challenges, cleaning your data and regularly checking your AI systems for fair results is crucial. It helps organizations prevent legal issues and protects their reputation and trust.

Transparency & Explainability

Do you know that most AI systems are black boxes? Didn’t know what a “black box” is? It is a scenario where a system takes a decision without answering the question “how.” The need of the hour is to overcome this challenge by providing explanations on how an AI system draws conclusions.

Data Privacy & Security

Securing data is another crucial factor to consider when using AI. Organizations can overcome privacy and security challenges by complying with international regulations like HIPAA in the US and GDPR in the EU for data protection.

Conclusion

The recent adoption of modern technologies like artificial intelligence in finance has reshaped the industry completely. It not only helps to improve operational efficiency and save time but also aids in decision-making and financial portfolio management. We can confidently say that utilizing AI isn’t just a basic need; it has become imperative for investment professionals in order to achieve greater returns.

About the Author:

Irfan Malik is pursuing a PhD in artificial intelligence and is the founder and CEO of Xeven Solutions. He’s tech-savvy and always stays one step ahead when embracing new technologies. He is passionate about solving real-world problems and is dedicated to making AI technology accessible and beneficial for all.

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Copyright: intelligencebriefing.substack.com – “AI Agents: Next-Wave Efficiency Across Your Business Systems Awaits”

On July 02, Jeremy Ravenel (Founder of naas.ai) joined Andreas Welsch on “What’s the BUZZ?” and shared how AI agents can assist businesses by understanding their core workflows. Despite the rush toward Generative AI, AI leaders need to be conscious of the known limitations of LLMs, the importance of mapping internal knowledge, and the impact of AI agents on improving front- and back-office operations. But where should you start? Here is what they’ve talked about…

Embracing the Ecosystem: LLMs and Beyond

LLMs like GPT-4 are powerful tools capable of processing and generating vast amounts of information, they shouldn’t be trusted blindly. The real strength is integrating these models into a broader ecosystem that includes your internal data and processes. LLMs bring a wealth of global knowledge into your business, but they must be combined with your unique business data to be truly effective.

Der Beitrag AI Agents: Next-Wave Efficiency Across Your Business Systems Awaits erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.