Microsoft is All In on AI

At Microsoft Ignite 2024, held on November 19, the company made significant announcements focused on its AI strategy, showcasing how AI will continue transforming workplace productivity, cloud infrastructure, and security. Here are the key highlights:

AI Agents and Copilot Enhancements

• Copilot Actions: Microsoft introduced Copilot Actions, a new feature for Microsoft 365 Copilot that automates repetitive tasks such as summarizing meeting actions, preparing reports, and managing schedules. These AI agents can operate autonomously once set up, running tasks without constant prompts.

• Autonomous AI Agents: Microsoft revealed autonomous agents that can act on users' behalf in the background. These agents plan, learn from processes, adapt to new conditions, and make decisions independently. They are designed to streamline workflows across platforms like SharePoint and Teams.

• Agent SDK: Developers can now use the Agent SDK to build custom AI agents that integrate with Azure AI and Microsoft’s Copilot services. This SDK allows for deploying multi-channel agents across platforms like Teams and third-party messaging apps.

Azure AI Foundry

• Azure AI Foundry: Microsoft introduced Azure AI Foundry, a platform for designing, managing, and deploying AI applications. The Foundry includes a portal for managing models and an SDK for integrating AI into business applications. It also offers tools for scaling AI agents and ensuring compliance with data privacy regulations.

• AI Agent Service: The Azure AI Agent Service will allow developers to orchestrate and scale AI agents to automate business processes.

Multimodal Capabilities

• Multimodal Agent Integration: Microsoft is enhancing Copilot Studio with multimodal capabilities. Agents will soon be able to analyze images and voice content in addition to text, allowing richer interaction across different media types.

AI-Powered Productivity Tools

• Teams Enhancements: New features in Teams include an Interpreter Agent that can replicate a user’s voice in up to nine languages for real-time translation during meetings. This feature will roll out in early 2025.

• PowerPoint Translation: PowerPoint users can use AI to translate entire presentations into other languages, further expanding the capabilities of Microsoft’s productivity suite.

Custom AI Chips

• Custom Silicon Chips: Microsoft announced two custom-made AI chips designed to enhance the performance of its data centers and reduce reliance on external suppliers like Nvidia. These chips will improve the speed of AI applications while bolstering security.

AI Security Initiatives

• Windows Security Overhaul: As part of its security push, Microsoft introduced new security measures for Windows systems to prevent incidents like the CrowdStrike breach. The updates include more robust controls over applications and drivers alongside antivirus processing.

Overall, Microsoft’s announcements at Ignite 2024 highlight its commitment to embedding AI deeper into enterprise workflows through autonomous agents, enhanced productivity tools, and custom infrastructure designed to scale AI securely.

AI helped me code a fully functional iOS app with no experience.

Today's 𝗕𝗿𝗲𝗮𝗸𝗳𝗮𝘀𝘁 𝘄𝗶𝘁𝗵 𝗔𝗜 mission was to code a native iOS app from scratch.

The app SafetyElephant provides real-time data on fires, earthquakes, and weather alerts near you or any region you plan to visit —all mapped, with details visible on demand.

The context:

(1) I have never built a Mobile App
(2) I have never used Xcode
(3) I have never used Swift

It sounds like a tall order ...

Well, I managed to build it. Check out how it all came together using Cursor AI and Xcode.

It was also a surprising amount of fun.

#AI #CEOsWhoCode #OldDogNewTricks

Leaning into Agentic AI

As I promised you last time, I would spend some time exploring Agentic AI. Sorry it has taken a few weeks, but it's been a bit hectic.

At any rate, I finished my first "Agentic" project on the flight home from London last night.

It's an app that allows you to enter any topic and have it debated (pro and con) by multiple AIs. Two AIs (Claude and OpenAI) debate each other, and a third (Perplexity running LLAMA) summarizes the debate (both points of contention and common ground) and comes up with a "winner."

In fairness, not all of this code was built on the flight, as I could leverage several components I had already assembled. However, the first cut of this app was ready in about five hours (or less than the flight time from London to Toronto).

Each time I experiment with AI, I get new ideas ... so ... wait until you see what I intend to build next. It's called Board Bot ... and it's coming soon to a board meeting near you 🙂

Enjoy!

#AgenticAI #CEOsWhoCode #ExploringAi

Notebook LM Magically Generates An AI Powered Podcast From 3 Documents

As some of you know, over the past couple of weeks, I have been running some AI-powered experiments:

If you are interested, you can read about them below:

Why am I doing this?

Well, (a) it is essential to get your hands on AI to understand its potential, (b) CEOs need to eat their own dog food if they are going to lead in this increasingly AI-accelerated world, and (c) it's my way of trying to understand the impact of AI across a software company's value chain.

What could a 𝘁𝗲𝗮𝗺 powered by AI do if I could do these things independently?

Last night, I tried something different.

Building on the INEA relaunch exercise over the weekend, I wanted to see if AI could help me create compelling content marketing—not in the form of dry, static documents but a dynamic AI-generated podcast.

The results were interesting ...

Can AI reimagine the launch of a 25 year old company?

As many of you will know, I recently published a few reflections on how AI has helped me code, prototype apps, and more in record time as a CEO who hasn't coded for 25 years.

I tried something very different this weekend. I went back to company and business plan creation ...

I asked AI to imagine the relaunch of INEA, a company I co-founded about 26 years ago, and to write a white paper covering what INEA might look like if it launched in 2025 as transformational performance management software for the financial services industry.

Could it be compelling and differentiated? If so, why? What would the product offering look like? What new technologies might it leverage? What would the TAM be? What would the competitive landscape be? What would the go-to-market strategy be?  What might the financial projections be? etc.

I gave it the only two legacy documents I could find, a brochure and an old copy of a business plan, and let it get to work. I even played the results of one AI off against another to refine the output.

The results astounded me. I achieved what would have taken us days or weeks before in a couple of hours.

AI is here ... and it is (already) changing everything ...

It's worth getting to know Daniel Miessler

Daniel Miessler's projects are interconnected efforts to address significant societal challenges through AI and open-source frameworks.

Miessler is concerned about three main issues:

• Lack of Purpose: Many people struggle with finding meaning in life, leading to mental health and societal issues.

• AI Disruption: Rapid AI advancements are causing work disruptions, potentially exacerbating this lack of purpose.

• Limited Human Development: People are trained to be economically useful rather than becoming well-rounded individuals.

His five significant projects aim to help people articulate their identities, improve themselves, and engage meaningfully with others. They emphasize clarity, transparency, continuous optimization, and purpose. AI is a central component due to its ability to identify patterns and provide insights across different contexts.

It’s worth reading this article, where he explains everything. If you wish, you can watch his summary of this work in the video below.

Substrate

• Purpose: An open-source framework to enhance understanding and problem-solving by making important issues transparent and discussable.

• Application: Provides a structure for shared understanding, allowing AI to analyze and generate insights on various human concerns.

Fabric

• Purpose: Simplifies the use of AI to solve everyday problems by providing a library of problem-solving use cases.

• Application: Helps with tasks like learning, decision-making, and optimizing daily life by reducing friction in AI tool usage.

Telos

• Purpose: Captures deep context about entities (individuals, teams, organizations) to improve understanding and management.

• Application: Allows AI to analyze an entity's goals and challenges, providing actionable insights and recommendations.

Daemon

• Purpose: An open-source framework for creating personal APIs.

• Application: Enables individuals to present their identity and capabilities as an API, enhancing personal branding and interaction.

Human 3.0

• Purpose: A framework for transitioning humans from traditional corporate roles to self-actualized individuals offering unique value.

• Components: This program includes video courses, assessments, and a maturity model to guide personal development toward becoming full-spectrum humans.

Beyond the interesting philosophical and societal challenges he touches on, his technology provides fascinating insights into AI's possibilities.

Understanding AI Security Risks: A Critical Imperative for Enterprises

As I have been exploring the accelerative power of AI in various forms over the past few months, I have been arriving at the conclusion that this is a form of grand sorcery. I jest … sort of … but in some respects I think this is an apt analogy.

Like all grand sorcery, AI is powerful stuff. But also, like all grand sorcery, we don't understand it well. It is becoming pretty clear that, in many respects, at this stage, we don't know what we don't know.

This applies, in particular, to securing AI in our enterprises.

There is a growing tension between our desire to use this powerful technology and the need to do so with the appropriate guard rails. To complicate things, emerging regulatory frameworks (the EU AI Act, for example) now have to be adhered to. The challenge for many enterprises in securing their companies and adhering to these frameworks is whether they have the technologies in place to help them meet these obligations.

The rise of Generative AI (GenAI) introduces a range of new vulnerabilities that malicious actors can exploit. As we integrate AI more deeply into our business operations, monitoring our use of AI, and understanding the security risks accompanying this powerful technology is crucial.

Let me give you some examples.

The Invisible Threat: Unicode Exploitation

A fascinating yet concerning aspect of AI security involves the exploitation of invisible text through quirks in the Unicode standard. AI models can recognize these invisible characters but remain unseen by human users, creating a covert channel for attackers to conceal and exfiltrate sensitive data. This vulnerability opens the door to prompt injection attacks, where hidden commands can be injected into AI prompts, potentially compromising confidential information.

The GenAI Attack Chain

To better understand how these vulnerabilities manifest, it’s essential to explore the GenAI attack chain, which outlines the steps attackers may take to exploit AI systems:

1. Bypassing Guardrails: Attackers often begin by circumventing the model’s built-in safeguards. Techniques such as encoding and token manipulation allow them to mask malicious inputs, making it easier to exploit system vulnerabilities.

2. Privilege Escalation: Once attackers bypass these defences, they can escalate their privileges through direct and indirect prompt injections. This enables unauthorized control over the model, leading to potential security compromises.

3. Security Compromise: The culmination of these actions can result in severe consequences, including sensitive data leakage, phishing attacks, and operational disruptions. Attackers can access critical systems, spread malicious code, and disrupt business operations.

Real-World Implications

Proof-of-concept attacks have demonstrated how invisible text can extract sensitive data from AI tools, such as Microsoft 365 Copilot. These incidents highlight the urgent need for organizations to prioritize understanding these security challenges. It's also becoming clear that sensitive data, including personally identifiable information (PII) and corporate secrets, can be exploited for identity theft or corporate espionage, leading to significant financial and reputational damage.

Addressing the Risks

As leaders, we must strike the right balance here. Find ways to embrace and leverage this technology while ensuring robust security measures and keeping people informed and well-educated about potential vulnerabilities. Understanding the GenAI attack chain and the risks associated with invisible text exploitation is critical for safeguarding sensitive information.

Conclusion

I'm pretty excited by AI's transformative capability. However, as we start to harness its potential, it’s imperative that we collectively understand and address the risks inherent in this new form of sorcery.

#AISecurity #EnterpriseAI #Cybersecurity #Innovation #Leadership

AI powered prototyping will change the way we conceive apps

AI has caused me to rethink a software product's ideation and prototyping phase. Let me explain.

Some of you will have been following my "How to teach an old dog new tricks" or "Can a CEO who hasn't coded for 25 years reignite his coding passion with AI?" posts over the past few weeks.

What I have learned from this has been quite transformational. It has caused me to reexamine my preconceptions of how we should develop software and what new market opportunities might be re-awakening for hyper-targeted vertical software. It has even forced me to rethink the structure of software startups moving forward.

This week, I'd like to explore how AI could transform a software project's ideation and prototyping phase ... skipping FIGMA and heading directly to a tactile prototype.

Take a look. What I am about to show you took just over 10 minutes.

#AI #ArtificialIntelligence #SoftwareDevelopment #Prototyping

AI is transforming interactions between clients and creatives

My wife and I re-designed and rebuilt our downtown Toronto garden not too long ago.

Because we had a pretty clear sense of what we wanted, we assembled a Pinterest board of ideas, and I drew a rough proposed layout in PowerPoint (don’t judge me; I’m a CEO, and I do everything in PowerPoint).

The team we worked with was superb. They took our clear wishes to heart (good-naturedly), and we were thrilled with the results.

I couldn’t help but feel that this process would have been even more straightforward with AI tools like Midjourney.

As an experiment, I embarked on another thought experiment to design a bright, modern and airy garden in a challenging urban space, surrounded on two sides by high walls (such as you might find in a city like London, England). The results after less than 5 minutes of effort are reflected in the image above.

AI democratizes creativity. It allows us to unlock our creativity without having to be craftsmen. It enables us to render a pretty close facsimile of what is in our heads, even if we cannot draw or paint. It can then allow us to validate whether specific components (plants, etc.) would work given location constraints, sun exposure, etc., without being horticultural experts. It can even write a project brief in a form familiar to the design/build team.

Fundamentally, AI can transform how clients and creatives interact throughout a project's lifecycle. Through real-time (interactive) visualization, collaboration can be streamlined from ideation to final execution. This can potentially drive radical improvements in the speed of iteration and (potentially) a reduction in design costs.

The trend of customers arriving with more fully developed concepts isn’t just restricted to the creative realm. One senior lawyer told me recently that clients are showing up with surprisingly good first drafts of contracts and requesting that those be vetted. That differs from yesterday's legal value chain, where law firms charged clients for creating those drafts and then for the refinement process.

As leaders, we must consider AI's growing impact on our companies. Will it be a force multiplier, competitive advantage, or existential threat? That’s really up to us.

Inviting Claude (AI) to Breakfast with BI

I often start my days with "Breakfast with BI." It's my chance to drill into the numbers behind the numbers—or the "why" behind the "what."

I have been thinking about creating a single dashboard with the key Enterprise SaaS metrics for some time now. So, I thought I would try something different for this morning's "Breakfast with BI" session.

In the spirit of my recent posts on "Can a CEO who hasn't coded in 25 years build an app with AI?" I invited Claude (AI) to "Breakfast with BI" this morning, and we collaborated on the Ultimate Enterprise SaaS Dashboard. As an added twist, I let Claude suggest the metrics.

Once again, the experience was enlightening.

And if you are interested, you can play with the final version of the app here. Noting that it is totally dummy and randomized data.

Caveat: It would likely have been more logical to do this manually (or with Copilot's help) in Fabric. But what would have been the fun in that?  😀

#LivingInTheFuture #AIGameChanger #CEOsWhoCode #AnyoneCanCode #DataIsTheNewOil

The madness of the founder mindset

Having started several companies, I can attest to the unique blend of thrill and despair that makes up the founder experience.

Being a startup founder can be a journey filled with exhilarating highs and crushing lows. Often, the thrill of building something from the ground up is matched only by the frustration of navigating the uncertainties and challenges that come with it.

It's often said that 90% of startups fail, but despite these odds, the few that succeed have revolutionized industries and changed the lives of so many. We need startups that push boundaries, unlock fresh solutions to age-old problems and birth radical new things never conceived before.

And for that, we need the founder mindset ...

While founders often experience an emotional rollercoaster filled with self-doubt and isolation, unlike most people, these moments fuel their determination and drive them to push boundaries.

They are just wired differently ...

They possess a unique blend of self-confidence and naiveté, which propels them to tackle challenges head-on. This "madness" that helps them take risks that others wouldn't is an unwavering belief in their vision.

And while the path of a startup founder is fraught with challenges, it is also a transformative journey that offers unparalleled rewards for those who persevere.

With everything I know, after many years leading companies from 5 people in a basement to 3,500 across 17 countries, would I do it again?

Of course.

And therein lies the magic of the Founder madness.

Can you code an App in the time it takes you to drive to the airport?

As some of you know, I posted a video earlier this week explaining how, as a CEO who hasn't coded in 25 years, I built an app using AI in the time it took me to fly from Vienna to Toronto.

One of my friends said:

"Pah! That's not that impressive. How about you build an app in the car in the time it takes you to get to the airport?"

Challenge accepted!

For those of you interested in seeing it here is the app.

And here is the story of how it was built in less than 40 minutes.

Legacy Enterprise Software is under siege by AI

I recently spent a fascinating few hours on a plane building software from scratch using AI. I did this as a thought experiment to get a more tangible sense (as a CEO) of the possibilities of AI-powered software development and to scratch a 25-year-old itch (I started my career writing a ton of code as a technical Founder/CEO and I have to say, I miss it sometimes).

It got me thinking a lot about how AI will affect the Enterprise Software industry, both positively and negatively. It also got me thinking about the implications of how we build software and software companies (but that is a post for another time).

AI will reshape the enterprise software industry, presenting challenges and opportunities for legacy companies. It will open up renewed avenues of competition from new entrants, potentially even customers themselves. It will also impact the expensive customization/integration model and the ecosystem of service companies that supply those services.

As AI enables faster development cycles and more personalized solutions, we could see a shift from generic SaaS models that rely on costly customizations to more tailored solutions (out of the box).

Klarna recently revealed that they have been using AI to develop bespoke, AI-powered solutions in-house, reducing reliance on generic platforms like Salesforce. Coupled with aggressive AI-powered automation, they are reducing both OPEX and FTE.

This is the Canary in the coal mine. It should drive legacy software companies to rethink their business models and product strategies. Not only must they innovate by integrating AI into their offerings, but they potentially need to revisit their entire pricing model.

There has always been and will always be the need to provide customized platforms that deliver specific value to unique customer use cases. But, the legacy model of taking a broad-brush, generic piece of software and leveraging expensive implementation resources to retrofit and customize it, sometimes costing 10X the product's price, is under siege.

The competitive landscape for legacy enterprise software companies will change as serious Vertical Software competition re-emerges. AI enables tightly targeted (niche) software companies with deep sectoral expertise to focus on hyper-specific use cases or verticals more efficiently. These (potentially lean, nimble) niche players can deliver specialized solutions previously uneconomical to pursue, offering tailored features that address unique industry needs ... and, in so doing, provide more significant ROI.

Enterprise Software companies have grown fat and happy charging high prices based on obscure, hard-to-understand pricing models. As competition rises from traditional and non-traditional sources, they will be forced to align pricing more closely with tangible customer ROI.

There are so many more implications, but that's for another post ...

#AI #EnterpriseSoftware #Innovation #BusinessTransformation #VerticalSaaS

Teaching an Old Dog new tricks

Here's an episode of "Can AI enable an old dog to learn new tricks?" Or can Mark, who hasn't coded for 25 years, write an app using AI during the time it takes him to fly from Vienna to Toronto?

Well, this was not only possible but also pretty revealing.

Besides passing the time on planes, doing things like this is essential for CEOs. With AI, in particular, you only really understand its true potential by getting your hands on it and experiencing its promise and/or current limitations in a tactile fashion.

Enjoy!

Vertical software is the new black

AI adoption has enormous potential to impact traditionally overlooked, “unsexy” industries.

These sectors are often burdened with chronic inefficiencies, high human capital costs, and low margins. They are ripe for innovation, and the first movers who can leverage AI to transform their businesses could shift meaningful enterprise value their way.

That makes software companies that can help drive this transformation potentially so valuable. And this is why so many VC funds are increasingly interested in investing in historically "unloved" vertical software segments.

Carpe Diem.

#AI #Innovation #TechTransformation #FutureOfWork #InvestmentOpportunities

Did OpenAI o1 just try to spin up a Replit instance on its own to test the solution I asked it to craft?

As a thought experiment, I had OpenAi o1 build a technical spec for an interesting (non-trivial) project. It made some interesting choices regarding tech platform, architecture, etc., and even provided some code snippets and a DB schema.

I then asked it for detailed instructions on deploying this on Replit, and I broke the system. It must have run out of resources or something. But what it tried (or at least appeared to be trying to do) stunned me.

See below for the train of thought … I was completely blown away ... surely it wasn't actually trying to spin up the instance itself? 🤔

#AI #AgenticAI #Intelligence

End the email chaos and migrate board interactions to a collaboration platform

I have found that eliminating email as the primary means of board communication and leveraging collaboration tools (such as Microsoft Teams) can streamline board processes, provide a secure and up-to-date repository of board documents and facilitate essential collaboration before, during and between meetings.

If you are a large private or public company with hyper-sensitive board materials, there are great board-specific platforms, such as Boardpro, OnBoard, or Diligent Boards. However, for most companies, creating a board-only space in your collaboration platform can provide excellent benefits.

I typically create a secure board-only space on Teams with three channels to start with:

• Meeting Materials & Financial Reports, including a chat space for discussion before and after board meetings.

• Policies and Procedures, including Board Charters (great for reviewing and signing off on policies).

• An ad-hoc area for special projects (great for strategic discussions, TAM analysis, market updates, competitive intelligence, etc.).

Regardless of your chosen approach, a collaboration platform provides critical benefits over email chaos:

• Acts as a central hub for communication, allowing board members to access meeting materials, agendas, minutes, and reports from a single platform. This ensures all members access the same information, reducing confusion and enhancing transparency.

• Promotes collaboration among board members regardless of their geographical location. Features like instant messaging, annotation, and voting enable real-time interaction and decision-making, fostering a more collaborative environment.

• Offers a secure platform for sharing sensitive information and protecting data from cyber threats. These systems often include document encryption and access controls, ensuring only authorized individuals can view or edit documents.

• Streamlines the organization and management of board meetings by simplifying the distribution of meeting materials and automating scheduling. This reduces administrative burdens and ensures that meetings are productive and focused.

• Ensures board members can receive real-time updates on important matters and access information anytime, anywhere. This flexibility ensures that board members are always informed and can respond promptly to emerging issues.

• Facilitates surveys and polls to gather feedback from board members, increasing engagement and participation. This helps boards stay aligned with strategic goals and fosters a culture of continuous improvement.

Choosing the appropriate tool hinges on various factors, such as the company's age and level of sophistication, whether publicly or privately held. Regardless, move away from email, and your board interaction will improve immeasurably.

OpenAI releases Strawberry and its potential is evident

Here’s a very approachable video describing what OpenAI’s o1 (Strawberry) is all about.

If our companies are to thrive in the new reality, we need to carefully understand the implications of this sort of technology and how quickly it is now evolving.

I just crafted the architecture and full technical specs for a sophisticated new feature we have been envisioning in less than 30 minutes. And it has been decades since I have developed technical specs, let alone coded.

The full suite of videos on the launch can be found here:

While Cypto Floundered, Serious Blockchain Projects Quietly Expanded

It’s been a rough 12-18 months for Crypto. But, as is always the case during “crypto winters,” serious work has continued behind the scenes on blockchain-related activities, including by national treasuries and major financial services firms.

I thought it would be worthwhile taking a look at what’s new.

Several major financial services firms have been adopting blockchain technology and in so doing, showcasing its potential to transform the industry:

• JP Morgan Chase: This financial giant has been actively exploring blockchain technology. It developed its own digital currency, JPM Coin, to facilitate instantaneous payments between institutional clients. JP Morgan's blockchain-based Interbank Information Network (IIN) was launched to improve the efficiency of cross-border payments by reducing the number of participants needed to verify a payment.

• Goldman Sachs: The firm has shown deepening interest in blockchain by investing in blockchain-related startups and exploring the use of blockchain for various financial services. Perhaps most interesting, Goldman Sachs has been involved in tokenization projects, which aim to digitize traditional assets like real estate or stocks, making them easier to trade and manage.

• BlackRock: Known for its significant influence in the investment management sector, BlackRock is investigating how blockchain can be used for asset management and trading. The firm sees potential in using blockchain technology to enhance transparency and efficiency in financial transactions.

• Fidelity Investments: Fidelity has pioneered incorporating blockchain into its operations by offering cryptocurrency custody services and exploring other blockchain applications. The company has launched Fidelity Digital Assets, a subsidiary providing institutional digital asset solutions.

• HSBC: This global bank uses blockchain technology for trade finance and foreign exchange transactions. HSBC's FX Everywhere platform leverages blockchain to settle foreign exchange trades, improving efficiency and reducing costs.

We’ve also seen growth in Stablecoin usage, particularly in emerging markets. From a recent newsletter by Linus Beliunas:

A recent survey revealed that while trading remains the top use case, many emerging market users leverage stablecoins for everyday financial activities. 47% of respondents use stablecoins to save money in dollars, 43% for efficient currency conversion, and 39% for yield generation.

Over the past six months, the issuance and development of Central Bank Digital Currencies (CBDCs) have also seen significant advancements across various countries:

The momentum behind CBDC development has remained strong, with several central banks progressing in their respective projects. For instance, the European Central Bank (ECB) has been actively developing its CBDC alongside countries like Argentina and Brazil, working on their legal frameworks and pilot phases.

• Specific Country Developments:

  • Argentina: The Central Bank of Argentina is developing a legal framework for its CBDC project, which aims to address economic issues and inflation.

  • Australia: Mastercard concluded a CBDC blockchain pilot with the Reserve Bank of Australia, although a full-scale CBDC is still years away.

  • Brazil: The Central Bank of Brazil has been working on the launch of the digital real (DREX), focusing on privacy and infrastructure issues.

  • China: The e-CNY was used in international crude oil trade, marking a significant step in cross-border trade using CBDCs.

  • India: The Reserve Bank of India is piloting its CBDC in the interbank borrowing market.

  • Philippines: The Philippines is advancing with a wholesale CBDC pilot to enhance large cross-border foreign currency transfers.

• Cross-Border Projects:

  • Project Mariana: This project involved central banks from France, Singapore, and Switzerland to test wholesale CBDC for cross-border trading and settlement using automatic market makers.

CBDC usage is likely to expand. A recent Bank for International Settlements (BIS) survey indicates an increasing likelihood of CBDC issuance among central banks. So, while many central banks are still cautious, a growing number see issuance as possible in the medium term.

AI continues to eat the world ... one finance bro at a time ...

A few weeks ago, JPMorgan Chase announced that it had taken another significant step into AI by developing and deploying its own AI-powered chatbot, the LLM Suite.

This tool, designed to assist with tasks like writing, idea generation, problem-solving, and document summarization, was being rolled out to about 50,000 employees in the asset and wealth management division.

JPMorgan has been making a significant investment in AI, and this move highlights JPMorgan’s continued integration of AI into its core operations. The firm appears to be doing much of this work internally rather than partnering with external platforms, as it feels that in-house development of its AI tools ensures stricter control over sensitive financial data.

Other firms, such as Goldman Sachs and Morgan Stanley, have also been leveraging AI to enhance productivity and streamline operations.

This all signals a broader industry trend toward AI adoption, potentially reshaping traditional roles within the financial industry.

JPMorgan chief executive Jamie Dimon told investors in May that AI would " change every job”. “It may eliminate some jobs. Some of it may create additional jobs,” Dimon said. “But you can’t envision one app, one database, or one job where it’s not going to help, aid or abet.”

Yup ... no argument from me ...

It does raise the question, though … for those of us embedding AI into our products, it’s important to support an open and federated approach, i.e. one that enables clients to embed their own AIs where relevant into the application workflows.

#AI #FinTech #Innovation #JPMorgan #ArtificialIntelligence #Productivity