Copyright: cio.com – “12 AI predictions for 2025”

This year we’ve seen AI move from pilots into production use cases. In 2025, they’ll expand into fully-scaled, enterprise-wide deployments.

Generative AI has seen faster and more widespread adoption than any other technology today, with many companies already seeing ROI and scaling up use cases into wide adoption.

Vendors are adding gen AI across the board to enterprise software products, and AI developers haven’t been idle this year either. We’ve also seen the emergence of agentic AI, multi-modal AI, reasoning AI, and open-source AI projects that rival those of the biggest commercial vendors.

According to a Bank of America survey of global research analysts and strategists released in September, 2024 was the year of ROI determination, and 2025 will be the year of enterprise AI adoption.

“Over the next five to 10 years, BofA Global Research expects gen AI to catalyze an evolution in corporate efficiency and productivity that may transform the global economy, as well as our lives,” says Vanessa Cook, content strategist for Bank of America Institute.

Small language models and edge computing

Most of the attention this year and last has been on the big language models —  specifically on ChatGPT in its various permutations, as well as competitors like Anthropic’s Claude and Meta’s Llama models. But for many business use cases, LLMs are overkill and are too expensive, and too slow, for practical use.

“Looking ahead to 2025, I expect small language models, specifically custom models, to become a more common solution for many businesses,” says Andrew Rabinovich, head of AI and ML at Upwork. LLMs aren’t just expensive, they’re also very broad, and not always relevant to specific industries, he says.

“Smaller models, on the other hand, are more tailored, allowing businesses to create AI systems that are precise, efficient, robust, and built around their unique needs,” he adds.[…]

Read more: www.cio.com

Der Beitrag 12 AI predictions for 2025 erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

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

Der Beitrag From Ethics to Efficiency: Successfully Scaling AI Across Industries erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

Building Tomorrow’s Tech: AI Investments in Full Swing – SwissCognitive AI Investment Radar

Welcome back to this week’s SwissCognitive AI Investment Radar, where we spotlight the latest in global AI investments shaping the tech landscape.

This week, we see a broad spectrum of strategic moves and financial commitments, from General Catalyst’s $8 billion leap into AI-driven enterprise transformation to Reflexivity’s $30 million for advancing AI-powered financial analysis. Across the Atlantic, the European Union pledges $1.5 billion for deep tech research, aiming to keep Europe competitive in an arena largely dominated by the U.S. and China.

Automotive innovation takes center stage as Toyota and NTT invest $3.3 billion to push forward predictive, accident-avoiding AI for self-driving cars by 2028. Meanwhile, Google’s $5.8 million initiative in Sub-Saharan Africa seeks to bridge the AI skills gap, enabling local talent to address challenges in health, climate, and more. AI’s influence is also reshaping sectors like architecture and construction, as industry players ramp up investments to integrate AI capabilities into their workflows.

From the defense sector, Helsing’s £350 million commitment underscores the importance of AI in national security, while Saudi Aramco’s VC arm dedicates $100 million to nurture AI startups. And as AI startups now command a third of U.S. venture funding, countries like Indonesia are positioning themselves as new hubs for AI with favorable policies and low energy costs.

Join us as we delve into these developments, capturing how AI’s financial momentum is redefining industries and shaping the future.

Previous SwissCognitive AI Radar: Tech Giants Lead AI Infrastructure, Startups Follow Suit.

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.

Der Beitrag Building Tomorrow’s Tech: AI Investments in Full Swing – SwissCognitive AI Investment Radar erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

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

Der Beitrag The Unexpected Role of Data to Unlock Generative AI Value erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

Tech Giants Lead AI Infrastructure, Startups Follow Suit – SwissCognitive AI Investment Radar

Welcome to the SwissCognitive AI Investment Radar, where we capture the latest global investments fueling artificial intelligence from Wednesday to Wednesday. This edition takes you from AI-powered infrastructure to green finance, showing how AI is shaping industries far and wide.

Generative AI remains at the forefront, with Magic raising $320 million to build the next wave of coding platforms. Meanwhile, Microsoft will soon allow clients to build their own autonomous Artificial Intelligence agents, further expanding the tech giant’s commitment to this burgeoning sector.

Private markets continue to show promise, with wealthy families and private banks pushing for AI-focused investments. On the sustainability front, AI is increasingly pivotal in driving green finance, helping create optimal portfolios for eco-friendly projects. However, while investments pour into Artificial Intelligence, the shortage of AI skills hampers its adoption, creating a disconnect between available funding and implementation success.

As AI continues to fuel productivity growth and even reshape talent retention strategies, the stakes have never been higher.

Read forward to know more about the major moves in the Artificial Intelligence landscape, from infrastructure to green finance, and how it’s evolving across industries.

Previous SwissCognitive AI Radar: Big Money and AI Trust Shake Markets.

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.

Der Beitrag Tech Giants Lead AI Infrastructure, Startups Follow Suit – SwissCognitive AI Investment Radar erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

Copyright: forbes.com – “Driving Real Business Value With Generative AI For SMBs And Beyond”

It’s no secret that generative artificial intelligence (AI) has enormous economic potential—McKinsey & Company projected that the benefits could total over $4.4 trillion in value for the global economy. But the dust is still settling after a frenzy of companies investing heavily in generative AI, and many are finding that ROI remains elusive.

Unsurprisingly, technology teams have been eager to experiment with various proof of concepts (POCs). But as Ben Schreiner, Head of AI and Modern Data Strategy Business Development at AWS, notes “The real sticking point has been getting POCs into production. This is partly because large language models (LLMs) are the Swiss army knives of technology—a tool capable of so many different tasks.” With such a huge scope of applications across product development, customer experiences, and much more, what makes generative AI so exciting is ironically what has stopped companies from getting the most value out of it.

“Many have struggled to focus on working backwards from a real business problem. Even once they’ve uncovered a well-defined business use case, failure to build internal alignment stunts ROI. To make investments pay off, a paradigm shift is needed,” Schreiner adds. His recommendation for driving generative AI’s revenue potential? “Companies of all sizes should pursue a purposeful strategy encompassing employees, business processes, and customers.”

Value Driver #1: Augment Your People

As the saying goes, time is money. From writing emails faster to automating menial tasks, the value lift of improving employee productivity is undeniable. But as Schreiner points out, “You can’t reach new levels of efficiency if your people feel uncomfortable about generative AI. Any barrier to adoption will be a barrier to business outcomes.” According to a recent Prosper Insights & Analytics survey, employees’ top three concerns about AI were that it needs human insight (32 percent), it can provide incorrect information (29 percent), and that it will cause job losses (27 percent).[…]

Read more: www.forbes.com

Der Beitrag Driving Real Business Value With Generative AI For SMBs And Beyond erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

Copyright: cio.com – “Top 7 Generative AI Use Cases For Business”

The launch of ChatGPT in November 2022 set off a generative AI gold rush, with companies scrambling to adopt the technology and demonstrate innovation.

Many of the AI use cases entrenched in business today use older, more established forms of AI, such as machine learning, or don’t take advantage of the “generative” capabilities of AI to generate text, pictures, and other data. Legacy chatbots, product recommendation engines, and several other useful tools may rely only on earlier forms of AI.

Some industries such as biotech are finding ways to use gen AI, but many enterprises experimenting with the technology have found a limited number of use cases so far, says Kjell Carlsson, head of AI strategy at Domino Data Lab, provider of an enterprise AI platform. For many enterprises the return on investment for gen AI is elusive, he says.

“The reality for a lot of users is that they just don’t have enough [information] to make an AI strategy leveraging generative AI use cases, and they’re not going to get to enough value quickly,” he adds. “They have a couple of use cases that they’re pushing heavily on, but they are building up this portfolio of traditional machine learning and ‘predictive’ AI use cases as well.”

Many AI experts say the current use cases for generative AI are just the tip of the iceberg. More uses cases will present themselves as gen AIs get more powerful and users get more creative with their experiments.

However, a handful of gen AI use cases are already bubbling up. Here’s a look at the most popular and promising.[…]

Read more: www.cio.com

Der Beitrag Top 7 Generative AI Use Cases For Business erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

Copyright: diginomica.com – “3 Steps To An Enterprise Gen AI Strategy That Delivers Real-World Business Results”

In a fast-paced global marketplace where the quality of data-driven decision-making regularly separates the ‘haves’ from the ‘have nots’, the ability to keep up with technological advancements is an essential aspect of managing a successful business. With the Artificial Intelligence (AI) boom of the last few years, business leaders are also being faced with a new set of challenges and opportunities. To make the most efficient use of generative AI (gen AI) tooling while mitigating the potential risk of their use, more and more organizations are formulating organization-wide gen AI strategies to better align the technology they use with the business OKRs they ostensibly serve.

At its most basic, a gen AI strategy refers to a strategic approach that incorporates AI technologies and tools to improve operations, enhance customer experience, and drive growth. With a terrain informed by myriad forces ranging from potential budget cuts to new rulings by the Federal Trade Commission (FTC) granting them the use of compulsory measures in investigations related to the use of AI, the imperative that CXOs and other C-Suite executives take ownership of AI-driven business outcomes provides another important justification for the development of coherent AI strategies. AI must be thought of not just as a tool for automating certain manual processes, but as a market-wide disruption that will reshape businesses down to their underlying operational models.

In this blog post, we’ll explore the reasons why having a gen AI strategy is crucial for your business and how it can give you a competitive edge in the market. We will also walk you through how to build your own AI strategy to make the most out of your AI investments. Finally, we will walk you through how Hakkoda has helped one Fortune 500 Consumer Packaged Goods (CPG) company strategically leverage artificial intelligence to streamline its reporting ecosystem and improve operational efficiencies in a modern data stack centered on Snowflake.

Step 1 – understand the risks of gen AI (and how to mitigate them)

The integration of artificial intelligence into your organization’s data practices comes with numerous benefits, but it also presents unique risks that need to be addressed.

One such risk is the potential for AI systems to make errors or provide inaccurate information. Since gen AI and LLM content is the by-product of vast amounts of training material, it is also worth being proactive in addressing discriminatory output, as AI will share any biases commonly found in its source data.[…]

Read more: www.diginomica.com

Der Beitrag 3 Steps To An Enterprise Gen AI Strategy That Delivers Real-World Business Results erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

The SwissCognitive AI Navigator: Practical Leadership Guide To Navigate The AI Era – Going Beyond Silo Mentality

Breaking Silos, Building Bridges – Collaboration on C-Level

With the relentless pace of technological evolution, it’s imperative for senior leaders to collaboratively discern the ramifications of these innovations on business dynamics, operational strategies, and workforce implications. Yet, a recurring challenge is the tendency of individuals, when confronted with rapidly advancing technologies, to feel daunted, leading them to disengage and opt for protective isolation. This behaviour isn’t limited to a specific tier but is observable across organizational hierarchies. As Peter Cunningham notes, “Amid rising ambiguity and intricacy, fear can manifest, driving individuals to curtail their involvement, seeking solace in isolation as a defence mechanism to conserve their assets.” Such defensive postures predominantly stem from apprehensions about the unknown. However, as Isabelle Flückiger insightfully suggests, “Our emphasis should transition from our anxieties to potential solutions.” Furthermore, while the synergy between humans and machines gains prominence, Dimitrios Kalogeropoulos highlights a critical perspective: “Before we prioritize human-machine collaborations, we must solidify human-human cooperation. True success entails humans working harmoniously first, and subsequently incorporating machines into the workflow.”

As complexities create uncertainties, the key is to focus on solutions, with a primary emphasis on strengthening human collaboration, before seamlessly integrating machine capabilities.

By fostering open communication and collaboration among C-level leaders, organizations can make well-informed decisions, allocate resources effectively, and align their technology adoption strategies with their overall business objectives. This collaboration ensures that all C-level leaders bring their domain expertise and perspectives to the table, enabling a holistic approach to technology implementation and avoiding siloed decision-making. It promotes a culture of innovation and adaptability, allowing organizations to stay ahead in the competitive landscape and navigate the complexities of the digital era.

By cultivating the usage of synergies at the executive level, organizations can navigate the digital transformation, fostering a culture of innovation and agility.

This collaborative approach will ensure a unified vision, helping break down siloed thinking, leading to integrated, comprehensive strategies. It will further foster an environment – not only on C-level but also beyond – that encourages the exchange of diverse insights and fostering creativity. Ultimately, this C-level and cross-functional engagement will help organizations stay agile, mitigate risks more effectively, and seize new opportunities in a rapidly changing business landscape.

Beyond the C-Suite: Engaging with the Heartbeat of the Organization

C-level leaders stand at a pivotal juncture, tasked with understanding the depths of AI integration across their organizations. It’s no longer a debate of if, but how and where to wield AI’s potential. As these leaders strategize, the workforce remains an invaluable asset, integral not just in high-level decisions but also in hands-on departmental tasks. As Dimitrios Kalogeropoulos pointed out, “Scaling can’t happen for as long as sustainable data management is not in place.” Echoing the sentiment on data’s centrality, Patrick Bangert remarked, “AI on its own is nothing. What is important is the data and the science behind it.” Meanwhile, Jürgen Pulm underscores the horizon, emphasizing, “The major focus in the coming years is on enhancing engineering capacity and capability, and with that preparing for the future.”

The harmony between humans and AI is more than collaboration; it’s a powerful partnership. Isabelle Flückiger elucidated, “Machines are better at processing large amounts of data and extracting valuable information. Humans are better at the interpretation of information and reasoning. The combination of AI and human are unbeatable.” Semih Kumluk extends this, stating, “The combination of human judgment and creativity with machine speed, stamina, and accuracy forms an unbeatable team in business.” Recognizing this dynamic interplay, leadership must champion the unique strengths of both, inspiring their teams to fully harness the combined might of man and machine.

Adopting a collaborative mindset not only builds confidence in AI but also underscores the unmatched significance of human discernment.

This approach not only optimizes productivity and decision-making but also fosters a positive work culture where AI is seen as an ally, not a threat. “Man plus machine, when appropriately combined, is indeed unbeatable. Education is critical to ensuring that humans maintain control over principles, while machines handle calculations and processing. Without proper education, the combined mistakes can be greater than those made by humans or machines alone.” (Jair Ribeiro)[…]

The exploration of AI’s vast impact and possibilities is just beginning! If you’re intrigued by what you’ve read so far, dive deeper with our detailed guide, the “AI Navigator”.

What is the “AI Navigator”?

An insight into AI’s evolving landscape. Ethical considerations, human-centric values, and practical leadership guidance, offering a balanced and in-depth perspective essential for any leader in today’s digital age.

To receive your complete copy, simply fill out the form below. In just a few moments, the “AI Navigator” will arrive in your mailbox, and you’ll be on your way to uncover AI, its potential, challenges, and the strategies for harnessing its power effectively in your organizational journey.

Chapter Contributors:

Alessandro Curioni, IBM Fellow, VP Europe and Africa and Director IBM Research, Zurich

Andrea Latino, Digital Lead, Innovation Growth Hacker, Nestlé

David Wood, Chair, London Futurists

Dimitrios Kalogeropoulos, CEO, Global Health & Digital Innovation Foundation, European Public Policy Committee, IEEE

Isabelle Flückiger, Non-Executive Board Member, AEW Energie | Vice Chairman of the Board Of Directors, Limmatkraftwerke | Expert for Innosuisse

Jair Ribeiro, Analytics and Insights Leader, Volvo Group

Jürgen Pulm, Chief Digital Information Officer, Wealth Business: Natwest Group | Non Executive Director, QESTIT (QCENTRIS)

Matt Hervey, AI and IP Expert; Head of Artificial Intelligence Law, Gowling WLG (UK) LLP | Co-editor General Editor of The Law of Artificial Intelligence

Patrick Bangert, Former VP of Strategic Business, SAMSUNG SDS | SVP Data, Analytics and AI, Searce Inc

Peter Cunningham, Head of Leadership Co-Director, Geneva Leadership Alliance

Robert Marcus, Founder and CEO, ALPHA10X

Semih Kumluk, Head of AI and Digital, PwC, United Arab Emirate

Der Beitrag Going Beyond Silo Mentality – The AI Navigator: Leadership Guide To The AI Era erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

The SwissCognitive AI Navigator: Practical Leadership Guide To Navigate The AI Era – Investing in AI – A Tripartite Approach

Investing in AI-Facilitating Infrastructure

The rapid evolution of artificial intelligence is transforming the business landscape, offering unprecedented opportunities for growth and innovation. In fact, “AI can be considered as alchemy — transmuting data into knowledge.” (Robert Marcus) As the benefits of AI become increasingly evident, organizations are looking for ways to effectively incorporate it into their operations. However, the mere adoption of AI technologies isn’t enough to guarantee success. Isabelle Flückiger emphasizes the importance of infrastructure, mentioning, “Many enterprises are directing their initial investment efforts towards building AI-supporting infrastructure, rather than just the technology itself.” This approach ensures that AI solutions can be effectively incorporated and scaled up.

A strategic approach to implementation, grounded in a solid infrastructure, is crucial.

However, the process of AI adoption is not without challenges. As Matt Hervey points out, blue chip corporations are heavily investing in AI, seeing its transformative potential, yet Jürgen Pulm observes that it still constitutes a modest part of technology investments. He predicts a steady growth rather than an abrupt shift in the AI landscape. AI is not a silver bullet solution that can instantly address all challenges. While it offers immense potential, its return on investment (ROI) may not be immediate. Patience and strategic implementation are essential to realize its full benefits over time.

True value isn’t just in immediate returns but in shaping discerning future investments for long-term gains in AI.

Despite all the enthusiasm, Morten Irgens adds that external factors such as economic instability and a frail banking system are hampering AI investments. Amid these challenges, industries are indeed treading carefully. Antonio Russo states, “Many companies are cautiously piloting these solutions.” For example, the health industry has been particularly cautious, especially due to the short-term (and very necessary) investments made during the COVID crisis, as highlighted by Dimitrios Kalogeropoulos.

Yet, Patrick Bangert remarks, “Despite all the challenges, AI now stands almost alone as the tech being invested in.” The rising startup activity in AI spaces, particularly generative AI these days, underscores this momentum. Aruna Patam discusses the emphasis on user-friendly AI interfaces, underlining the importance of practical applications in both business and personal spheres. Alessandro Curioni notes the shift in AI investment focus from data value to model value, emphasizing the importance of understanding these models.

With these changing dynamics, companies need to balance short-term gains with long-term sustainability. As Bo Percival states, “Diversified investments strengthen societal resilience and encourage innovation that benefits all.” Jarrod Anderson also envisions AI investment focusing on solutions that elevate societal living standards and address larger issues. AI’s potential impact on sectors like healthcare, education, and sustainability cannot be overlooked, promising not only societal benefits but also robust economic growth. The role of AI in addressing global challenges, especially the environmental crisis, is also coming to the fore. While Robert Marcus clarifies that AI won’t directly resolve climate change, it can undoubtedly accelerate innovations that mitigate its effects.

It’s essential to understand and harness AI not just for immediate business advantages, but for its potential transformative influence on the broader societal trajectory.

As industries increasingly embrace and venture further into the realm of artificial intelligence, encountering setbacks is a natural part of the evolutionary process. These hurdles are not just barriers; they are invaluable lessons. As Jair Ribeiro insightfully puts it, “In AI investments, setbacks today pave paths for wiser tomorrows.” This perspective highlights the importance of reframing our understanding of these challenges. Embracing a mindset of continuous learning and adapting can transform these apparent setbacks into genuine opportunities. This adaptive approach can guide the trajectory of AI, ensuring that it is steered towards a future that not only promises immense growth and groundbreaking innovation but also fosters a sustainable environment that benefits every stakeholder involved. The resilience and foresight this perspective offers can truly revolutionize the AI landscape.[…]

The exploration of AI’s vast impact and possibilities is just beginning! If you’re intrigued by what you’ve read so far, dive deeper with our detailed guide, the “AI Navigator”.

What is the “AI Navigator”?

An insight into AI’s evolving landscape. Ethical considerations, human-centric values, and practical leadership guidance, offering a balanced and in-depth perspective essential for any leader in today’s digital age.

To receive your complete copy, simply fill out the form below. In just a few moments, the “AI Navigator” will arrive in your mailbox, and you’ll be on your way to uncover AI, its potential, challenges, and the strategies for harnessing its power effectively in your organizational journey.

Chapter Contributors:

Alessandro Curioni, IBM Fellow, VP Europe and Africa and Director IBM Research, Zurich

Antonio Russo, Head of Strategy and Analytics, Deloitte Switzerland

Aruna Patam, Head – Generative AI Practice, Insights & Data, Asia Pacific Region, Capgemini

Bo Percival, Senior Adviser, Innovation (Ventures), UNICEF

Dimitrios Kalogeropoulos, CEO, Global Health & Digital Innovation Foundation, European Public Policy Committee, IEEE

Isabelle Flückiger, Non-Executive Board Member, AEW Energie | Vice Chairman of the Board Of Directors, Limmatkraftwerke | Expert for Innosuisse

Jair Ribeiro, Analytics and Insights Leader, Volvo Group

Jarrod Anderson, Global Head of Artificial Intelligence, Senior Director, ADM

Jürgen Pulm, Chief Digital Information Officer, Wealth Business: Natwest Group | Non Executive Director, QESTIT (QCENTRIS)

Matt Hervey, AI and IP Expert; Head of Artificial Intelligence Law, Gowling WLG (UK) LLP | Co-editor General Editor of The Law of Artificial Intelligence

Morten Irgens, Strategic Director to the presidents (rectors) of Oslo Metropolitan University and Kristiania University College, Director, CLAIRE, Adra and NORA

Peter Cunningham, Head of Leadership Co-Director, Geneva Leadership Alliance

Robert Marcus, Founder and CEO, ALPHA10X

Semih Kumluk, Head of AI and Digital, PwC, United Arab Emirate

Der Beitrag Investing in AI – A Tripartite Approach – The AI Navigator: Leadership Guide To The AI Era erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.