Dec 24: Crisis or Crypto Christmas?

This newsletter is a combination of my own analysis and insights, informed by publicly available information and industry trends.

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.

It’s intended to come on a monthly to 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.

Starting with the chipset market, this remains a hot topic to continue to update also this month.

• Nvidia is keeping the rally of developing further even if encountered some problems with the heating of the Blackwall chipset and even if different analysts raised the fair stock value that is anyway still exchanged much higher than the recommended value. 
• I feel this will still keep raising. Many semi-conductors depending on automotive market are suffering and this is not going to change on the short. More in the EU Crisis sub-section.
• TSMC, as you remember I mentioned on former newsletters how much is relevant on the semiconductors supply chain, just quickly replied after Trump tariffs announcement, they would not see any impact on the final products selling pricing. They are at this stage accelerating on their main plans for having full production (in Taiwan) in 2025 on 2nm and in 2026 on 1.6nm. I’m curious, based on the big connection and dependency on US what will happen if they will receive a push to start to produce 2nm in US. That is something I would expect to come especially if friction between China and Taiwan would increase. As I referred in the former newsletters, the dependency from many players from TSMC is high and will be interesting to see how the market will adjust to reduce the risk. Their stock is suffering at this time but they are from my perspective a good deal on the long term having so much diversified ecosystem of customers and so advanced technology.
• On the cpu market, Intel and AMD seem competing and AMD surpassing Intel when we speak about datacenter cpu and I still believe some consolidation will go to happen in the future. 
• Just reminding that Qualcomm stock is still under pressure until around Christmas (60 days deadline from ARM from the 23rd of October). You can find more in the former newsletter release. If the conclusion will be successful, like I believe, Qualcomm should ramp up decent well.

Speaking about big techs also linked to AI:

• In October we had the earnings update for the Q3 for Microsoft, Google, Amazon as I reported in the former Newsletter but in November we saw the effect of the election on the Tech companies. Amazon got a good burst, as well initially Google that only recently got impacted by the Chrome selling proposing coming from the US Department of Defense. Microsoft, from their side struggled instead to gain stock traction. The market is not recognizing the ROI from the AI investments.
• Gartner, during its annual Symposium in Barcelona main event, communicated the fact the AI is tending to the end of the hype phase that is then following the usual disillusion phase. In short this means also that within the next year, many companies will realize first tangible results from first AI initiatives and will have better view on their ROI. In the section below for AI Risks I detailed this more.
• What could happen?: I speculate here on the fact that the former and future US president, was also in tight fight with tech companies in the last mandate around immigration bans (here for example an article from 2019). I feel the actual trend seems to try to take away some of the power those tech enterprises gained so far and be sure they would not be a problem with the immigration plans. It looks to me like starting back where the conversation was left last time.
• Future US president near end of November released also on his comms platform that he would once in power, apply a 25% tariff on the import from Mexico and Canada and raise the one with China for another 10%. Europe should stay, based on former exchanges on 20% tariff. December will be the time of the main US importers are going to try to get as much as possible goods before the new tariffs come in place (technically after the 20th of January 2025).

Also news in the crypto market

• Final for this summary, the many messages about future US investment in Crypto that made a big bounce for many crypto with Bitcoin reaching near 100K$ and many others raising their value of 2-3 times in a couple of weeks. I keep a detailed analysis on Crypto in a separated section below.

The recent US elections will go to put more pressure to the European Union members in terms of exports tariffs to export from Europe to US and the general de-regulations will influence how the tech services from US will come to be perceived in Europe. Take for the example the recent regulations of European AI Act that will be fully operative within 2 years. A tighter control form Europe could influence the decision to prioritize or less the investment in direction of this market from US enterprises. 

• We saw the case for example recently of Apple deciding to postpone Apple Intelligence introduction in Europe to better comply with EU regulations. Similarly Google to comply with EU Digital Markets Act on its search engine. 
• On the other side I like to remember that European Union has also developed a strong culture around privacy, human rights and environment care and the way to build new capabilities is not happening following the same path and speed of some other countries. To attach one example to this, again in November we saw Musk asking to people to upload personal medical data to X to train his AI (Grok) engine and get medical recommendations, having clearly said that such data could be also shared with third-parties. The tendency to feed AI environment with data not always completely balanced in term of privacy and sensible content can be a fire-back once those data are used to train the engine too. As you understand, Europe starts from a different way to attack such aspects and the consideration around privacy is strong.
• At the same time, the cars market crisis in Europe, extends to other connected businesses providing automotive parts (like Bosch) and the renewal energy businesses get influenced by the new oil drilling US politics coming.

In the area of energy and how this impacts environments some interesting news

• The energy business seems having an important change influencing also all those businesses depending on that. The big techs are going to be great requestors for energy in the future and the limits of energy deliverable thru the countries power grids is pushing the topic of finding other sources, near the datacenters, approaching micro-grids with nuclear plants and new micro-nuclear reactors able to switch off in milliseconds in case of problems. Also Gartner in the recent Barcelona Symposium mentioned as one of key initiatives. I mentioned longly in November’s newsletter about the possible effects I would see and some reference links and questions I raised. From that time anyway, for example Amazon got blockedon its intention to push for nuclear own production for the time being. I’m curious if hydrogen power plants will have a chance to be progressively ramping-up in the overall game of CO2 reduction and increasing energy demand, increasing energy and reducing CO2 at the same time. 
• Concern I have is instead to go back to produce energy “the old way” and introduce concepts of geoengineering but without proper research also on possible side-effects as there is much attention from China (at COP29 still classified as developing market) and by US.
• In November there was also the COP29 in Baku with several feedback about failure to get proper alignment and missed important presence and not sure how better is going to be supported in the next upcoming years.
• It’s interesting to see that part of the energy consumption we are demanding is caused by AI future needs and the hype around it could go down as we progress and leave with a case of energy surplus. 
• At the same time also crypto currencies are going up and also here a huge energy consumption to keep block-chains consistent. It’s clear that the future is energy demanding and also clear that will cause a non-linear demand and not necessarily distributed in a uniform way cross the world. 
• As I mentioned in last month newsletter, many AI activities remain strictly geographic specific as no real fully distributed algorithms are applicable to the full machine learning process to distribute the workloads cross regions.

November was a big hype on crypto. Interesting effects linked to future quantum Computing. What happened after US election seems really interesting

• The SEC responsible in US left having no alignment with new government strategy and making more confidence on the acceptance in the future for crypto currencies in a less challenging way.
• The overall Bitcoin and altcoins had a huge increase. Especially some altcoins raised 100-150% in 3 weeks.
• Behind there is a big confidence from the expected bigger investment from US Government from next year in Bitcoin and speculations raising on building even pensions fund with part in Bitcoin (here in UK for example) as already started in the summer in Michigan. That seems quite risky approach from how I see but is telling about how some realities are trying to overcome past gaps in their financing.
• Still in November, the presence of Elon Musk in the new US leading team showed big influence on Tesla stock (rose more than 30% in days) and then in the meme crypto Dogecoin (DOGE as stock name as his new US department). I don’t comment here apart that each one should analyze what a meme crypto is and understand which value is behind it, if any. Different topic for those crypto that have a real purpose.
• What could happen?: I see a Crypto rally until Christmas and January but also quite unstable and risky, depending on how long the US Government keep on investing in Bitcoin and how much other crypto currencies will be considered
• There is an explosion of new crypto currencies and as well of new meme coins making the overall investments diluted over several solutions
• Specularly a possible Christmas Crisis because as much as the Crypto can be an opportunity, it will be a threat as happened to many investors that went  short of Bitcoin and lost big amounts too.
• What could happen?: The other threat to Crypto on the long I see is the Quantum Computing that will require an evolution in the crypto blockchains to be quantum hacking safe. So is relevant that who invest on the long on crypto is also considering that such market will be progressively influenced by the underlying blockchains reliability.
• What could happen?: Other consideration and correlation is that crypto currencies evolution will be not without a serious energy impact and we saw already that energy demand, micro-grids and new energies ways are themes quite sensible where we have serious impact together with AI. Energy consumption is going to be to the stars considering the mix of higher demand coming AI and blockchains.

On a more general news perspective:

• Gartner reported recently in Barcelona that only 48% of digital initiatives are successful. 
• When we look around AI initiatives the rate of failure ramp up from several analysts and Gartner over 80%. 
• An aspect I’m sensible to report from few months is the risk of costs explosion linked to AI adoption if not proper ROI is done estimating also the evolution of the costs of consuming AI capabilities as the data sources and requests will grow. I was referring that already in October and then in November newsletter as my concern that would erode the IT ops budget. As reported now by CIO.com here, referring to Gartner analysis, I see this concern is getting more concrete especially when we look to the expected forecasted costs. As visible from the link, Gartner analyst estimates possible miscalculation up to 1000% so 10x time the original budget cost for an AI solution from CIOs. I’m not feeling that is a wrong estimation indeed because the cost prediction for such solutions is highly influenced by the training engine, the data quality and amount, the level of queries and sources and many variables that in a POC could be too optimistically estimated or missing many other conditions.
• So here is my warning about the introduction of AI with a proper TCO evaluation and to build a proper business case in early stage and highly before phase of production and then later continue to monitor its evolution.
• Like I wrote last month on the rise of Agentic AI, the market of Agentic AI just started with for example Salesforce advancing on their Agentforce, Microsoft announcing their Copilot Autonomous just after the Ignite, SAP ramping with its Joule and many others. So far we discussed around LLM but the agentic, combining the LLM and all the RPA and introducing a level of autonomous have a much bigger impact than what we saw so far with bare GenAI.
• At the end the concept of Autonomous Agents is not new. It was a paradigm already defined during the time of my university studies in CS in 1998 and in my master thesis of software engineering, combining my specialization in distributed systems, I was addressing the underlying base of communication based on webservice (part of what is today SOA) with the purpose to create an interoperable, distributed, loosely-coupled architecture combining business workflow modeling, able to be distributed in the way to interact and decide. 
• Today we see the legacy with monolithic and predictable environment on one side, the loosely coupled with geographic localization in the middle with for example micro-services and the fully distributed, loosely-coupled and autonomous on the other extreme side that is getting now more interesting with the LLM part of AI. From my perspective we are at the start of the trip
• Gartner reported “By 2028, 33% of enterprise software applications will include agentic AI, up from less than 1% in 2024, enabling 15% of day-to-day work decisions made autonomously“. This is a relevant statement and seem to me reliable and can help to make the maths about efficiency to gain in operations but requires a conscious way to be introduced and I just mentioned few example of risk in the AI Risks section.

Looking to future trends linked to AI:

• Agentic AI is going to transform the ERP segment in terms of part of the processes to be fully autonomous in term of evaluation and autonomous decision. It’s expected to be applicable also on processes more crucial because based on more accurate internal data
• The CRM part is based on data less precise and not always same quality like ERP so the autonomous can be connected to specific subsets of processes where possible automation could be considered. So far well developed the post sales processes, mostly customer care related. I see companies speaking mostly of chat avatar as their main AI agent but here that is for me the real starting point. I’m sure here it will be interesting to see some of the capabilities for example from Salesforce’s Agentforce.
• The OT part has a big area of capability. The trend on the market is to have OT more integrated with IT and because of the different lifecycle, there is a good autonomous agent opportunity especially linked to digital twins for preventive maintenance for example
• The part of shared functions for me has a strong opportunity with Agentic AI. Procurement processes more autonomous, we already mentioned and SAP Joule and some HR processes, especially on the hiring and more administrative tasks (linked to questions from employees like self-service for recurring administrative tasks)
• Please remember that an autonomous agent combines RPA, LLM and also memory for being able to create a seamless experience, realizing the automation and autonomous decision on different business workflows.

On a totally different topic, it’s always important from my perspective also to look back and remember that we live in a digital world and if we don’t design it properly, we can land in a non-functional environment. Just I say this to keep attention when we speak about implementing IT technologies, about the side effects of some critical infrastructure. 

• Specific case I want to mention is the one of Denmark that in November due to a mobile down, got completely blocked in many critical services and operations showing a quite dependency situation on the critical infrastructure. This is making me concern how fragile would be our environment under a byzantine case, meaning a case with the purpose to generate panic and not a failure like in this case.

The actual situation in the market, especially the European one is clearly indicating some industries developing but many industries either restructuring, either holding decisions for US new strategy from next year and a common sense of uncertainty that is causing stuck in moving. I always thought that not deciding is like deciding to not doing anything and bring anyway consequences.

There are those negative on the market speaking about a crisis like 2008 with the difference that at that time the energy cost was not high like is today. I tend to think that crisis is an opportunity time to make the things differently and get advantage from a special situation. Steve Jobs once interviewed on how to manage during crisis time was referring that last thing he was focusing was on lay-off (due to the effort taken to hire good people) and rather funding and investing in R&D to come out of the crisis stronger and ahead of competitors. Now the 2009 was the year in which we had a big explosion of first cloud providers and SaaS solutions started to get wider on the market. So here some reminders why Digital Transformation is mostly needed during difficult time:

• A company Administrative and non operational costs can be highly optimized by automation.
• IT spend during crisis should be funded in the area of RPA and maintenance to allow other departments to develop their capabilities of automation and guarantee supported environments during the next ramp up.
• Business operations can benefit from automation (RPA) and from analytics consolidation to better predict future spending based on historical data.
• Business operations can improve from proper digitalization of processes and consequent effective process mining.
• Support (Shared) functions are crucial to a digital transformation because for example HR, Finance and Procurement key processes need to embed with Ops and Sales to make efficient end 2 end processes.
• Building end2end business processes integrated and with data aggregated to allow consistent analysis and forecast, is crucial to achieve informed decisions.
• Crisis time and low volumes is the ideal time to close gaps in technology and reduce quickly IT risks that can be much more hard to solve during peak time.
• Autonomous agents can accelerate the RPA, introducing also autonomous decision capabilities during Digital Transformation. More in Agentic AI section.

I can’t speak about AI capabilities and Autonomous Agents without giving a note to how much is relevant to make such type of initiatives properly implemented, always tracking the risks during the full lifecycle of projects and then of operations.

At the recent Ignite Microsoft anticipated the risks of the new Copilot Autonomous indeed coming with a set of best practice how to avoid oversharing and risking, for example, that a sensible HR information is shared with all employees.

Here I want to remind that:

• new technologies, especially AI related and GenAI can create the disillusion that a thinking brain is behind evaluating what make sense and what not to do or to share but there is an human regia needed to guarantee a proper control and progressive training of such type of technologies
• any IT technology implemented without the proper attention and without preparing for “what to do in case of” is going to be risky.
• the Microsoft recent documentation is showing most probably how much risk is perceived by the IT giant in term of wrong data sharing that could come from enterprises once using such type of capabilities. Here a good short summary too.
• AI solutions remain machine learning platforms, capable to predict behavior based on how good we fed them in training and can bring bias based on how the data are generated and fed, how some inferences are deducted and which models are used. In my former newsletter I tackle some of these cases.