Apr 25: Q1 2025 – Tariffs and Summary of main Technology Trends

This newsletter is a combination of my own analysis and insights, informed by publicly available information and industry trends. It’s my own manually written work and hope can benefit in term of authentic and creative content creation.

All my comments represent my personal opinions about Digital, Data and Technology trends in enterprises, based on the news we can all read and my correlations for further conversation and exchange always constructive and respectful.

My comments on crypto or stock market are intended as bare speculations about what I suspect could happen and why but are not intended to be recommendation for market investments and I’m not an expert in the field. I recommend to refer to specialized investor experts for your wealth management.

This newsletter It’s intended to come on a monthly/quarterly cadence based on the relevant topics I believe make sense to share and will keep a structure as much as possible technology and vendor agnostic. I could miss to identify some relevant topics that were somehow not in my radar of regular read. Feel free to suggest further arguments missed or to keep an eye on.

A part “What could happen?“ to give future predictions and correlations for the upcoming months and a section “So what?” to comment on former guesses and how they went.

A part with Revenue Opportunity or Costs Optimization/Ops Excellence or Risk Avoidance as three highlights that can be found in some sections when I see hints in how Technology could be used to achieve those aspects

The hints I recommend represent just a minimal fraction of the possible ideas (the what) I could suggest and there are several ways to apply them (the how) based on different variables, conditions and prerequisites part of my consulting analysis and execution. Each business is different and best practices help us to define the base on which we can build up the extra unique value.

Why can’t comment? I just left intentionally only comments to do on Linkedin to have one single place to exchange.

• Intel got a new CEO and the strategy will go around re-energizing the Intel Foundry, working as outsourcer for brands like Nvidia and Qualcomm and restructuring the part of the company too much inefficient. The potential benefits go also in the direction of accelerating production back in US of semi-conductors, giving a further pressure to TSMC that is already aiming in producing more in US the 2nm and potentially the 1.6nm as formerly discussed.
• Q12025 Summary: the first quarter showed a big competition for the semi-conductors supremacy and their production back to US. The pitch we saw from JD Vance on the Venture Capitalist event in March is to combine production and design in US, bringing back innovation under US supremacy. I analyze more in the section on Job Evolution because I think the pitch is quite valid on some areas, especially related to innovation vs stagnation from cheap labor but I put in the equation also feasibility from workforce point of view and how that could be approached. Finally, I just remind that will come the  AI Chipset export restriction from the former US Administration within the first 120 days of the year and this will be on top of any tariffs strategy.

The most recent tariffs discussion from the new USA Administration is posing a clear topic on the dependency of each other market and the synergies lost. If on the usual market (steel, coil, etc) is possible to have different sourcing, when we land to discuss around technology, there is a strong dependency on the US market on tech services and there is today no real option to balance without a proper homework that would take many years to create autonomy.

Looking to how Europe, and big part of world, is depending on US technology, we can see that over the last 30 years US built a strong ecosystem that for example Europe consumed from without creating a proper alternative base. China in the last 10+ years built some level of technology independence building own OS for mobile phones and having some other OS for computers based on forks mostly of Linux and other infrastructure services with own technology. China also built own semiconductors, chipset and AI as well datacenters. Most recently also Europe spoke about the wish to have an EU Operating system but let me say the things are more complex than just an OS.

When I wrote in October last year in my newsletter on the evolution of the market with the EU Crisis and the Draghi’s receipt for transformation, I mentioned that Draghi was considering the last 30 years of US development in technology a huge advantage that could be not anymore closed by EU in some areas like Clouds but could be worked out in the AI. Looking now to the tariffs (that don’t apply today to services but only to tangible goods), there is an important element to consider from two aspects, one related to the cost of a service that could be raised in the future (i.e. applying tariffs to cloud usage) but even more relevant the risk to be “disconnected” by a service operated by a company in a country with a different relationship (i.e. recent Starlink discussion), impacting on the own sovereignty of each country.

Technologies are built on layers, making more and more level of abstraction and making users not seeing the underlying complexity and enjoying easy way to use. However each layer is done by one or more technology and the dependency on a stack of technology is defining the dependency on who is producing and maintaining that stack. Without landing in doing an ISO-OSI stack comparison, let me use an easy example to make it understandable to everyone:

• Physical/Backbone: Most of network equipments are US (i.e. Cisco) from hardware and technology and most of the infrastructure globally run on these technologies. Alternatives vendors are often US based or have dependency in their chipset, architecture, protocols (each network device has chipsets) on US vendors (again we have Intel, AMD and in the area of network there are also decent European entities and Chinese but still US is big here)
• Datacenters: Run on US Operating Systems (limited by some open source with Linux and some good EU alternatives for Linux solutions) and run on US Virtualization layers (where we can exclude again some of the open source)
• Storage and Chipset: Many US but also where we have alternatives, the OS of those storage run not always proprietary.
• Clouds: They run on Datacenters so even if they are in EU and from an EU vendor, they depend on what they have inside on US technologies.
• SaaS applications: They run on Clouds so they depend again on that layer before.
• End users: Run mostly on US OS (including mobile phones OS) and devices (here we have alternatives but the hardware chipsets are again mostly US)
• Application level: Here I don’t want to even start. Just remind yourself your work suite on your PC and think which provider built it. Then we have security layers etc. etc with many presences from US.
• Data and AI: Sit on top of the others. So all the other layers influence them.

I stop to make further layers explanation but we could do that more deep and more accurate. Definitely we will have exception, definitely we could build a certain stack with minimal or no dependency on US but would represent a specific case that is not reflecting the most enterprises and even consumer reality we have today. Here I just mentioned technology services but any physical product using those services is also influenced by that. I take one as example that is the automotive market that is more and more cloud and tech connected and many technologies of those cars run on cloud of US and with technologies from US. This can spare to other type of products where there is a technology inside. I just want to make clear how tight and interconnected we are with technology that has been built and developed accurately by US with a lot of influence and evolution from rest of the world and that brought over the last 30 years a lot of innovation. China, that worked over the last 10 years on reducing the dependency, definitely has still some areas to decouple but worked out already on chipset layers, worked on OS layer and I expect some level of virtualization and storage including OS. Also worked out to reduce security layers depending on US technologies as this would be strategic in a cyberwar. All this to say, that a fight to decouple dependency is long, big and is requiring long investments to try to reach the same level of maturity we have today. In the section on Job Evolution, I evaluate how the production back to US could be influenced by Technology to be achieved considering the equation of job labor needs and cost mitigation for inflation.

• So far I saw mostly a decent level of marketing against meme coins. Many people experienced to lose money in such type of game and stopped to invest in it. This is for me a good result as I care to have small investors not ending in such traps. Other crypto coins are suffering as we mentioned last month and will most probably continue for some time such trend. There is an up and down as more investments are promised in the direction of Bitcoin and so far it seems this will be the only real crypto to be sponsored by US government. I still have no clarity around the stable coins.
• Q12025 Summary: The first quarter has shown a big change in the crypto market, from last year ramping up (until mid January) to highest levels and then sinking really fast in February, together with the many new meme that accelerated the negative hype versus the entire crypto market. However the real crypto currencies have a certain meaning even if at the moment seems that investment from US government is mostly oriented in the Bitcoin only direction. I always recommend to diversificate and use crypto only in small parts of investments.

• On the micro-reactor energy production, we see some progresses ongoing for example also in US. The need of distributed energy near datacenters without impacting on the grid distribution is going to accelerate.
• Similarly in the area of nuclear energy by fusion, we see startup ramping up also with the focus to refactor former fission nuclear plants, like happening in Germany.
• Q12025 Summary: Some progresses in the area of fusion nuclear and micro-nuclear reactors for fission in real small reactors. This quarter saw the acceleration of alternative energy production sources to compensate the big demand from different areas. Fusion seems progressing over the quarter with 10x times ability to keep plasma controlled to support fusion and China is leading record after former France achievement. This seems promising to get real in the next 10 years. Meanwhile the production of micro-reactors with minimal time to switch off and reduced risk of fissile drop is growing. There is a clear race for energy production lead and considering this as the requirement to lead the AI revolution. US is highly focused on this lead.

• Some companies like Apple kept their focus and support on the DEI so far and is giving a certain stability in their organization. However showed recently some opening on the privacy aspects that were a key reference of their brand. I just reflect if these will influence the internal opinion on the enterprise like happened with Google (as I mentioned in former newsletter)

• So what:? Microsoft announced in March that they are delaying to build some AI datacenters as they are also announcing they will adopt the improvements coming from DeepSeek. This was my prediction in the newsletter of two months ago related to January and is going to influence the overall Tech investments as the market is getting more efficient to deliver AI. This is going to democratize AI.
• The most recent Deepseek V3 runs also on consumer hardware. This is going to impact definitely the need of stronger hardware and clouds and could decelerate the Nvidia race even if they were having a pipeline of demands already filled for years.
• Costs Optimization: I keep reminding to have a continuous check on the AI pricing and avoiding too long big commitment as this pricing will drop .
• Q1 2025 Summary: We saw a ramp up around discussion of agentic as they are developing more as independent solutions. At the same time, Trump administration is cutting many jobs in the government and announced they want to build up more high salary jobs in US, combining design and manufacturing. A first insight from me here below but then in the Job Evolution section I analyze in deep how the AI could influence the Job Evolution market with tariffs.
• What could happen?: I predict that the jobs gap in US (already open jobs) extended by the need of more advanced jobs to bring back full integrated products lifecycle in US, will create a challenge on availability of resources and how to keep anyway labor costs low to keep the overall products affordable. The way I see this formula could fit is to use agentic and robotics to make manufacturing much more autonomous (not just automatic but Industry 5.0) and higher salary jobs on the top of the chain to grow this structured. So my view here is that big part of the gap of many jobs expected, could be covered but by autonomous agents (physical and not). I make a deep dive reflection on this in the section of Job Evolution.

• There is still an acceleration on the conversation around humanoid robots, trained with AI and learning to walk and move more like humans. Even few tests for early adopters to have a humanoid at home like the Swedish brand 1X is trying to do. Still to clarify how people like to have such presence in their home either for privacy reasons (camera watching) either for human safeness confidence.
• What could happen?: I just don’t challenge AI safeness at this stage but I challenge the capability of a tech environment to be not hacked. What would happen if a hacker would take control of a remote robot and would force to do actions that should be not done? We always reflect on how guarantee that a AI is not acting wrongly and there is a consensus on its way to operate but there is still the byzantin fault, as bad actor that could influence the way to operate of such autonomous agents in thousand ways. The AI governance and in general the freedom of such equipment to walk and be autonomous in actions on the premise of houses or fabrics need to be properly thought. Today we have automatic actions, robots with specific tasks and areas of coverage and are predictable and with specific purpose, not generic, open way.

• Recent training of OpenAI ChatGPT with Hayao Miyazaki, building Ghibli style AI images, got viral and pushed OpenAI to suspend as copyright concerns come out. The solution was really brilliant and come out really nice models but the point of copyright goes back on something I’m saying from many months in the newsletter on the training of AI engines and how to guarantee proper respect of the sources. This is definitely not a case only of OpenAI as we see many other AI engines and LLM built also with techniques of distilling that are losing the original source of training data references. I reported these concerns for many months, referred also to the regulations that need to be in place and on which Europe with the AI Act started to define formally, in the governance of how and what has been used to train an AI. This is even more sensible as we do that in the boundary of an enterprise keeping attention also on reputation.

• Q12025 Summary: We saw an acceleration on the overall Quantum Computing thru the approach to reduce/mitigate errors creation rather than trying to build bigger engines. The strategy to reduce errors as modularly combining and extending power is going in the direction of enlarging power and progressively distributing and reducing the risk of error generation in the results. Quantum Computing is preparing for a real revolution in power to compute (billion times faster than the most powerful super-computer) giving capabilities in areas like complex medicine and biology computations, potentially solving NP-Complex algorithms but also posing a threat on overall security making much easier to crack most advanced encryption techniques unless properly adjusted. In the next 3 years, Gartner as I mentioned in the former newsletter, is highly recommending to invest to update applications to PQC (Post Quantum Cryptography) to be in compliance with future security requirements. This is a big investment that is not necessarily on the radar yet for each enterprise as it should.

This month I want to reflect on the Job Evolution due to Technology taking in consideration few base documents for the conversation:

• The Future of Job (World Economic Forum 2025)
• A New Future of Work (McKinsey)
• The future of European competitiveness
• The population pyramids by 2030 and beyond
• The JD Vance recent pitch at American Dynamist Summit

Take this as short analysis and is not planning to be comprehensive. I recommend to take the read of the links I shared as there is much knowledge available in those references.

So what are my takeaways from the read as I cross those figures? Please accept I focus only on the technological and not political component as that is my interest area.

Starting from the pitch of JD Vance few weeks ago is clear that US Administration wants to bring back production to US as this is going to bring back more control on the US driven innovation. The pitch is quite effective in explaining the recent history effects of globalization from the innovation point of view, mentioning that cheap labor from outside US has been a way to make products more attractive rather than really innovating. So the effect of production outside US brought progressively more design also outside US, reducing the innovation supremacy. Listening the overall presentation, there is a clear focus on bringing back stability also in workforce as deindustrialization is seen as risk for security of the nation. The tariffs are the reflection of a way to protect US workforce from the cheap labor and there are consideration that productivity didn’t increase in those countries that pushed in the past for cheap labor.

As the presentation progresses, the cheap labor is seen as problem also with illegal immigration that is accelerating it. The way to operate effectively for enterprises that want to innovate avoiding cheap labor is thru automation as he describes. The formula to bring back innovation in US is making manufacturing back, using automation instead of cheap labor and making energy cost lower to make more competitive local production.

Looking more the trend we see from the population pyramids we see that Europe is in a trend of already shrinking population, as well China, where the trend is more mitigated in US.

Combining the WEF analysis by 2030 and the data from McKinsey by 2030, we can see some commonality and few minor divergences.

Focusing on the main similarities, there is a clear trend speaking about more jobs in the future than today while the actual jobs are different than the future ones. Looking to the low wages jobs and the mid and high wages jobs, there is a clear reduction of the first ones and increase of the last two ones. This means that cheap labor in EU and US also locally will be not growing but rather reducing and will be a clear need of upskilling people to be able to take jobs with higher complexity. Basically low wages jobs that are quite manual and repeating are in the focus to be automated, especially if are those jobs that today are done by outside as cheap labor.

Looking to the McKinsey report is also clear that Europe could increase 2-3% of productivity each year if they would have a more consistent technology and digitalization adoption where US already embraced that more systematically in the last 30 years.

Literally McKinsey says “European companies lag behind US peers on multiple key metrics, such as return on invested capital, revenue growth, capital expenditure, and R&D. Initial delays in Europe in technology development and adoption help explain this gap, as Europe did not benefit from the information communications and technology–driven productivity advancements that have occurred in the United States since the 1990s”.

What could happen?: From my angle, is quite visible that US businesses and now also Middle East are more advanced in incorporating technology driven functions in key positions in organizations where Europe is often seeing still some of these as support functions unless related to the end products and even in those cases with strong limitations. The acceleration on automation and as next progresses on the autonomous agents and AI is simple making this gap even bigger from my perspective as enterprises in Europe are stalling on the old organizational and operating models, posing also on technology investments an attention not systematically strategic. However, what I see unrealistic in the US administration tariffs approach is the massive automation in a real short term that would be needed to achieve that type of production back in US and accelerated by the tariffs strategy. Here is where I see a risk to simple build a wave of missed jobs coverage while autonomous operations is not yet mature enough to scale up in a real short time.

Looking to the actual US trends, the illegal immigration restriction and the production back, will accelerate the need of resources on the US borders, paying taxes in US and producing for US. Having today already a gap of more than 2M jobs not covered, this means that there will be an even higher need of jobs covered in US in the future. The raise of low jobs to medium raise instead of automation will be not an option because would ramp up dramatically the cost of producing goods. The gap is going to be covered by automation as also written clearly from all the reports. It’s about 27-30% of activities that are going to be automated, mainly the most repetitive per industry or the ones more commonly operating cross different industries (i.e. office admin). It’s at the end the productivity gain to make more with less but need to be achieved in a structured way.

In the WEF report, looking to skills and job less needed in the future, manual jobs remain only on those cases that are really specific and vertical, not justifying an automation due to the specialization but those are normally not cheap labor.

What could happen?: The trend we saw recently accelerating on humanoids robots and the acceleration on Industry 5.0 with collaboration between robots and people with robots more autonomous, seems going to be the formula to match the need to have more resources to produce locally in US autonomously without impacting on productivity and using cheap labor.

This could be a formula to allow to grow still in an economy that would need to get many more jobs covered as they would move production back. However there are considerations to do on the fact that, reducing low wages, basically automating, and pushing on higher wages jobs, require to accelerate on upskilling with all the restrictions and limits of those. The reskilling (so changing completely roles and competences) could be even more complex in that sense. McKinsey speaks about 60% of upskill where WEF in some cases up to 80%.

Seeking the Industries, as I mentioned in the last few months taking the example from the WEF, some businesses with high level of intrinsic digitalization (like banks, insurance) are set to reach high level of automation (only AI) and small amount of manual (People) or augmented (People with AI) jobs. Jobs in chemical and oil and gas, are set to reach high level of automation removing even augmented roles (so either some manual either automated). Jobs in healthcare, in government, in advanced manufacturing and energy result having the lowest rate of automation (still considerable) and keep the highest level of either manual (with complex specialized tasks) or augmented roles (people with AI). In the middle there are many industries that are clearly automating and the more are on low margin in the value chain, the more push for automation. In this sense we see transportation where digital supply chain get key, as well mining, automotive, tech companies, good manufacturing, and agriculture. For detail look for the WEF and for my former newsletters.

What is quite impressing is the prediction on the timing of this change. As all the reports mention, it’s about the next 5 years until 2030 to achieve this level of automation and job upskilling for a considerable number of jobs (170 million jobs projected to be created and 92 million jobs to be displaced). Some jobs are set to reduce considerable like office support and manual jobs and agriculture is one of those with more disruption in the way to work with many jobs created but also displaced, meaning a change of generation and way to work. In the McKinsey the sales rep roles get much more reduced versus the WEF report (that sees displaces but also bigger creation as change of way to work) but still mean a considerable change in some of those roles that are more repetitive and can be automated.

McKinsey writes rightly from my point of view “Occupations with lower wages are likely to see reductions in demand, and workers will need to acquire new skills to transition to better-paying work. If that doesn’t happen, there is a risk of a more polarized labor market, with more higher-wage jobs than workers and too many workers for existing lower-wage jobs.”

The overall acceleration on AI is seen as way to match the gap of the needed automation to compensate the growing demands. From this is coming the demand for a low complex and regulated AI to quickly develop further.

What could happen?: An AI Governance should exist and be consistent, not blocking but not even missed to be fast. Copyrights on data training is one element but I’m more focused on the behavior of autonomous engines and the difficulty to deduct the origin of behavior. We speak and support ideas of AI agents for autonomous decisions but the monitoring of the process from automation to autonomous need to be properly industrialized. We took years to raise RPA, so robotics process automation that is indeed quite easy automation on predictable process, eventually learned. Autonomous is bringing a level of autonomy in adjusting the automation processes and can be powerful also in the progress of deep and reinforcement learning but also requires control at least until a certain maturity is in place. If not properly governed, a wrong behavior can motivate a stop and lose of trust in the overall technology. At the end an AI is a stochastic engine, it’s not empathic, it can be probabilistically reasonable and we need to learn to use them properly as we do for example when we take decisions based on statistics.