Nov 24: The rise of Agentic AI

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.

I maintain also a weekly updated free channel called MindForIT where you can get ad hoc articles and posts that are part of the base for the newsletter.

I was speculating in October’s newsletter on the continuous development of some brands in the AI chipsets.

• Here we spoke in first line about Nvidia that, with also sponsor from big players like Microsoft, Google, Amazon, were hitting a new peak in stock market. 
• At the same time Nvidia announced in October that the new production line for the AI most powerful chipset Blackwall is already fully booked until end of 2025 indicating clear gaps between market demand and needs. Interesting to see also announcements for example from Microsoft, just one week later, on the collaboration with AMD that indeed seems entering in the competition with Nvidia and clearly big cloud providers are interested to reduce risk of single sourcing.
• Intel announced they will not try to compete with Nvidia top range lines with their Gaudi 3 chipset due to the much more advanced status Nvidia is at this time and so they will focus more on the lower lines competing on price per performance versus the equivalent lower line of Nvidia and other competitors. On top, they showed improvement versus the former fiscal quarter and that gave positive results on the stock value.
• Qualcomm on its side, apart speaking about collaborating with AMD on strengthening their power against Nvidia, has a strong roadmap also in the area of more powerful chipsets for automotive. I will speak about that in the section about cars below. Said that, Qualcomm was last month influenced on the stock by the dispute with ARM for the license to use their architecture for chipsets. ARM gave 60 days to solve the dispute or forbidding the possibility to produce further chipsets.
• What could happen?: This clearly impacted on the stock of Qualcomm but my bet, please take as not speculation and not expert, is that the issue will be solved and Qualcomm will get thru on the stock value. Reason is how they answered in the communications and the solid roadmap they have behind with many product lines that I expect will bring a solution on the table. On top to consider that a dispute not solved on the ARM would deny the production of chipset for many android devices within 60 days.
• All these chipset players but also cloud providers with cloud servers chipsets, computers and phone companies like Apple with its M and A chipsets, depend strongly on one single player, TSMC, Taiwan headquartered (with all the influences of that with actual geopolitical situation) due to their advanced production processes. The interesting production plans for TSMC include one more production factory in US by next year and with the other factory in development in Dresden (Germany). These will be two interesting hubs for all those future needs and more distributed workloads.
• Interesting side-note that in October US government raised the concern that TSMC would have produced on the US territory, parts for Huawei and that would be an infraction of the actual regulations. Interesting to see how this is going to be solved and how could be influenced by US elections considering the history of US and Huawei past conversations and restrictions. Clearly TSMC is working hard to proof they are doing the best to avoid such type of case. For example recent update of identification from TSMC on Huawei case that received a lot of attention.
• What could happen?: Definitely I still believe like last month, that some consolidations between AMD, Qualcomm, Intel could happen but not clear in the timing and if this will get real. For sure there are some level of partnership like Intel with Samsung in this sense. 
• There is an interesting story with ST Microelectronics that made not good earnings results neither has good outlook for the 2025 and is on restructuring but at the same time seem having opportunities in the cars market, especially in China, and curious to see how will develop further on top with possible AI and health sensors. Interesting that Intel, delegating activities to TSMC in areas where they are missing competences, are at the same time making wrong steps in communicating about the relation with TSMC, killing the discount they got for such outsourced activities.
• For sure there is a market opportunity especially in advanced AI chipsets, with a leading player (NVidia) being fully booked for production requests for the next 15 months and not able to take further orders at this time for some specific top lines and a semiconductor player (TSMC) having the most advanced miniaturization and leading on the market but being also a single point of failure. Final note on TSMC, their US production will not run the highest density transistors level that will remain in the leading technology sites in Taiwan for the time being.
• Speaking about AI market forecast, we saw with the end of October and the earnings update from Microsoft, Google, Amazon, Apple some interesting trends. Microsoft overachieved the analysts plan but the stock value dropped more than 5% as indication of concern on the investments in AI not monetizing and possible influence on the Azure future trends. Google on the other side ramped up a little bit, probably as indication of more confidence and also related to former situation improved. Amazon was also running well. It seems that investors fear the hype of AI in terms of investments not recognized by real value generation. This was especially the case of Meta that was indeed over-achieving on earnings but at the same time considered over-spending on the AI hype. At the end Meta less than 2 years ago was fully focused on Metaverse (not forgetting the brand name change), spending around 46B$ on thatand the change of focus was highly impacting also an important number of employees. It seems quite clear that the AI investments go tight with high value in some businesses like Pharma like I also mentioned in my October’s newsletter. Some more reflections on this are also in the new section named Science and Social below.

In the area of AI we have many recent updates that are interesting to mention. The hype on AI is still quite high and there are many conversations that big part of these initiatives will not survive after the end of the hype in mid future.

• One relevant element for this month in terms of hype, also title of this newsletter, it’s the ramp up of the AI Agents. Now trying to be pragmatic in explanation, the AI Agents look to me interesting as concept that is in principle bringing some level of former robotic automation augmented with GenAI but then augmented with more autonomous capability, moving from a static, rules based approach, typical from an RPA to a behavior approach based on description of the purpose of the agent making it able to adapt to the requests and also able to execute more autonomous activities potentially fully e2e and in some way take decisions for some business processes. It’s interesting in this sense the announcement done by Marc Benioff, CEO of Salesforce about its AgentForce in October at Fortune after his initial announcement in September again on Fortune. There is clearly some pressure to deliver AI in the evolution of Sales tools in terms of real value add and in September Marc was speaking much about the possible future trend to have AI agents to operate on behalf of sales employees, introducing even the concept of a license not anymore per user but per AI agent. 
• In October he moved more in direction to attack Microsoft for its Copilot, as side effect, in my opinion, due to the announcement just few days before from Microsoft on the integration of Copilot GenAI capabilities in its Dynamic 365, competing in the same segment. An advantage I see here is that on one side Salesforce has strong data from its customers and long experience in this field and that could build proper AI Agents on top for automating, improving sales decisions where Microsoft could deliver that experience across multiple components of their ecosystem, up to data layers and office but maybe would require more work to integrate.
• Parallel, ServiceNow, playing more and more as platform of platforms pushed also strongly in the direction of AI Agents that could allow to have some pieces of processes automated and integrated with GenAI. For sure that could be interesting in areas where some business processes got already implemented or planned to be implemented in such platforms and make some automation. I’m also thinking to a typical case like growing automatically knowledge base of an enterprise thru AI Agents just to mention one. 
• As well SAP with its Joule is playing in the area of AI Agents automation, with an interesting hype on procurement processes, that seems to me quite beneficial as improvement to prioritize.
• Other case quite obvious is linked to software coding AI agents not anymore assisting but mainstream in code development.
• The proof of the pudding will be in how much these agents will be able to reduce repetitive activities while interacting with GenAI capabilities and how well they will be able to play in the process of autonomous decision, based on the training, to accept or deny in decisions process. For example there are activities around having some processes of insurance managed by AI Agents that in some cases would work to take decisions but would have a second level human approval. Also activities in the healthcare with NVidia in terms of AI Agents to execute avatar driven hospitality. On the other hand it will be also sensible to set boundary where these agents will not be effective. 
• I’m reflecting, and here is one of my correlations, on the Apple’s research that also recently is progressing on the limits of mathematical capabilities of LLM in terms of interpretation. I’m in this sense thinking how important will be to set limits until where AI Agent will be able to take decisions with mathematical interpretation thru GenAI, initially restricting areas of application and progressively evolving as the models will develop further. Just to make a brutal basic example, no-one would trust to have an healthcare AI agent providing recommendation on pills doses based on a GenAI conversation of symptoms that could have a mathematical bias and indicating wrong quantities.
• I see some good business cases for example using AI Agents to automatically feed internal knowledge base evaluating which contents would be interesting to be aggregated. Here different players would have different advantages to make this effective as one of the core capabilities of an enterprise. Another one would be customer services, sales ordering, procurement as already mentioned, hiring processes and possible data consolidation. 
• When I look to the bare IT support processes, an acceleration about AI agents is already happening from years, first few years ago with chatbots, then last year with automatic tickets GenAI summarizing and automatic knowledge base and now progressing in automatic tickets interpretation and process automation.
• One more reflection here on the AI Agents, but here my thinking is more blur, would be to use such agents not only to make full automated business processes but helping to build and maintain updated and consistent interfaces between applications implementing a business process and data consolidation across structured data, including data cleansing activities.In this sense I see benefits on more repetitive tasks as mentioned before and as well on datalake/data mesh level for example to help to identify and expose relevant data to be made available for publishing. 
• Where I see another area of interest and is tight with the part of interfaces/integration is in the area of IoT, but for this I have a new separated section below. 
• The other area where I would see AI Agents is in the HRIS hiring platforms and job applications platforms and you can find more described in the section below on HR Platforms. There are already aspects of AI contents moderation for example in platforms replacing employees for their activities. You can find more details in the section Science and Social where I elaborate on the effects of AI automation and job market on a specific case in social network platforms.
• Continuing on activities automation, an interesting recent update is from Anthropic, a famous Open-AI competitor that just announced a way to make many activities happening behind a screen of a computer automated thru an AI recognition engine with GenAI. In this sense, also Microsoft played with its highly controversial Recall going in that direction even if started more from a time-machine approach. What we can see is that many administrative activities done by employees on a computer, could be automated, especially if they are repetitive but not only, if they follow certain paths. I can imagine this will allow to improve process mining activities for all those areas that today are not fully managed in ERP and are human intervention based but would also play a risky behavior in monitoring activities executed by employees on computers. So the opportunity and the privacy risks will have to be managed accurately and seem clear to me that edge of application will be quite tight.
• Also important for the AI Hype will remain the aspects of intellectual property. I mentioned in the October’s Newsletter on the risk of AI Mad due to train AI with data coming from AI. Interesting in this sense the effort from Deepmind to set watermarks in text to identify when AI generated. As we will progress, I believe will be more and more techniques to watermark and to go around intellectual property contents and that will impact the AI training and capabilities we will see developing and the consequent reliability on bias in decisions.

• It was interesting last month to see aspects related to power of computation benefits where thanks to the advances in GPU capabilities, a researcher, former Nvidia employee, worked out to identifya new biggest prime number, 16 millions digits bigger than the former one, part of the 52 known Marsenne prime numbers. This was somehow also driven by the big hype of AI that developed the GPU market to the next level.
• Also in October theNobel Prize for Chemical was won by co-founder and by the Director of Deepmind, thanks to the software with AI capabilities built that is able to predict 3D structure of proteins from their amino acid sequences. This shows how much the AI and especially Pharma are in general tight connected on the development of the most advanced area of AI capabilities that can bring real value. Similar capabilities develop in the area of new materials and will generate other values streams in Chemicals and R&D of other industries. There are on the other side other activities in the Healthcare and AI where the GenAI could bring value but also fear based on job cut but also on bias in evaluations. Here the transformation happening too fast and without proper attention would impact seriously on reputation of those firms not properly building and training their AI platforms.

In the Social we saw:

• It seems that the AI already generated some aspects of redundancy in low mature markets wherecontents moderation moved already to AI managed for social network platform Tiktok.
• There is a big hype coming now on the remote work reduction strategies hiding a silent firing strategy driven by AI automation introduction. There is a clear sensibility on how this will evolve and just last month I was speculating on the too aggressive back to work with zero remote strategies, especially reflecting on new GenZ attitude. That could fire back as businesses will lose efficiency if the AI automation will not bring practical benefits at the level of scale expected. At the end the workforce have more flexibility to adjust their activities than a vertical AI agent so the risk to anticipate reductions based on AI hype will cause, from my point of view, risk to lose flexibility versus future needs. I think it will be crucial to make a proper process, transitioning to new employees roles while AI will take on more repetitive activities and adjust organizations sizing according.
• In the Environment instead we saw:
• Interesting that I referred last month to the grow of electrical consumption from Microsoft due to AI and the wish to restart some old nuclear plants.At the same time, also pushed by the impossibility to wait for long decisional processes from government, also Google and Amazon are pushing in the direction of own nuclear energy production, based on small nuclear plants near the datacenters, also allowing less impact and dependency on the whole grid. It’s coming to me few questions, one for example, how this will be secure, also from a military point of view. If before the datacenters would be sensible targets to attack data, computing power and connectivity to companies, this is going to introduce a new possible sensibility type even if these are mini-nuclear reactors. It’s also interesting for me to understand if this verticalization of market where an IT company starts to produce own energy will bring later on the other part of the equation the fact, these companies will start also to influence energy production and delivery market.
• However out of all this, it remains my core question that I raised from August. What will happen with datacenters in those countries that decided to go against nuclear? For example Germany and what about those countries like Italy, where Microsoft announced last month that they will invest 4.2B$ to build datacenters in the next two years, considering that they will have no nuclear plants possibilities? Will be this going to impact on the overall energy capabilities, will impact on the cost of the services that, if hosted in those countries will have a completely different cost? Will this push the change of strategy of some countries in terms of nuclear usage? Will this slowdown the evolution of Clouds and AI in those countries?
• One of the challenges in the datacenters grow is due to the fact many of the AI activities require strong interconnection so, are not planned to be executed on geographic distribution so limiting the max capacity of computation by plant. There are some algorithm that could be built to be fully distributed at a certain stage or for example the phase of training of AI could be distributed and that would reduce the physical restrictions, allowing to run computation cross geographic datacenters but it seems still on an early stage of development and not necessarily feasible on a large scale of algorithms. Definitely could have a strong influence on the overall strategy of datacenters AI capabilities deliver and is an element I would keep an eye.

In the IoT world there has been an interesting update coming last month. 

• On one side the 5G seem not having taken much on the market in terms of usage versus investments from telco and some speak about the 6G that is far to be yet on the market but an interesting element that is raising is aboutthe eSim raise for IoT. This is today existing in around 30% of IoT devices but there is a clear trend that seems going to raise heavily in 2025 also driven by the opportunity to make such connections more reliable and behind all this could change also the complexity to have different devices having proper connection and integration to specific clouds to feed data fabrics with less edge complexity. Here I like to remind that 80% of the data of a company are NOT the bare ERP data and the OT represent a big portion of that 80%. So relevant is to consider that a Data strategy designing how to feed data in one or more concentrators and transform, has to also design a proper correlated AI concept. 
• I strongly think that an AI strategy can’t decouple from a clear Data strategy as base. So in this sense, as I was mentioning in the AI section, there is big chance of transformation to come to the IoT world in terms of automation of processing and transformation with GenAI capabilities. Here I think will be valuable to have eSim capabilities to make more flexible to maintain updated and in sync big variety of IoT equipment and the AI Agents could help to make a good first consolidation/clean on data at the edge level (so speaking more on edge computing in this sense).

However, having 70% of equipment not yet capable to work with eSim will require most probably a lifecycle of replacement that will continue over the next 5 years. So in this sense I’m not sure how quickly the IoT part will evolve worldwide with new capabilities but definitely interesting to keep an eye and consider linked to strategy of OT standardization also from security point of view.

In the electrical we have seen that the announcements from Elon on his expected volumes for next year caused a +20% in few hours of the stock of Tesla and BYD that is making a quite consistent roadmap evolution of its segment and earnings. 

• Limiting to what is relevant on technology trends change, an interesting announcement from Qualcomm goes in the direction of predicting a bigger volume of technology hardware for cars coming in the future. Their roadmap is filled with many chipsets with low consumption and higher performance to allow to maintain several screens and sensors in a car also with limited cloud connectivity as edge equipment, feeding with many data a central unit of transformation. This would allow to generate stronger smarter contents and capabilities in the cars, like sensing by the feeling of people and their speak, the need to change some set up (i.e. someone feeling cold, saying in the car to someone and getting automatically his/her section of car with temperature adjustment). 
• The car segment is under stagnation in Europe, also due to the entry cost of cars, especially on the electrical segment and is interesting to see what will be the relevant customers trends in this sense. There was less than 6 months ago an analysis reporting that a certain amount of people felt distracted by so much technology and screens so the future in this sense has to be adjusted and the profound market stress in this area could bring some changes. 
• Anyway, looking to announcements, seems that ST Microelectronics would benefit from China’s needs in terms of semiconductors in the automotive so also here interesting to keep an eye on the market evolution coming especially from Asia.

Right in my former Newsletter of October, I was referring to the missed presence of any quantum computing Center of excellence in Europe, as also Draghi was mentioning in his report, considering out of 10, 5 were in US and 4 in China.

• Announcement of October that in Germany, IBM will start the first Quantum Computing datacenter. I think this will be important for the European competitiveness but will require to bring innovation and technology in the hands of the European lead rather than being an US hosted and owned only innovation. 

The quantum computing is relevant today for many researches, especially in materials and molecules analysis and simulations. It will get more hype as will combine more with AI. I generated for that sense a free channel speaking about Machine Learning and Quantum Computing named MacQuantum that I update only on specific ad hoc cases contents I think can be relevant.

Over the last few months we saw the ramp up of automated AI solutions with GenAI. In the October’s newsletter I mentioned the future trends related to Human Digital Twins and the progressive combination of human personalized contents aggregating personal data related to health, wellbeing and work. You can see more details in the former newsletter.

Looking more on the specific aspects linked to jobs market, there is from my perspective a ramp up in the generation of personalized job applications, including per customer application automatic cover letters. 

• There are several platforms already on the market that are getting more capable to integrate with platforms for job posting and able to personalize with GenAI to fulfill the full application process, including cover letters. Some of these solutions aim to achieve even more than 750 applications submitted per day. Some real users experiences speak about automating around 20 applications per hour reaching a total of near 3000 applications automatically applied including GenAI generated cover letters personalized for each firm and role. This is for me bringing an obvious new element that even if enterprises have already implemented an advanced HRIS Hiring engine with AI, there will be a progressively more AI to AI triggered interface where the AI solutions to find jobs, will hook how to rate their paying users, to make them succeeding in passing the first filter of job application. Unless properly organized and filtered, there is a big risk from my perspective, to stress the HR organizations of firms to manage the wave of applications that could make a match. This will ramp up, again from my perspective, as the GenZ will be more on the market and will look to apply to jobs in an easier from their perspective way. There is a common opinion that GenZ have less patience, also driven by the flow of datas they manage and the time to react they got used to and this could make them quite fast willing to find easy ways to access to market, rather than thru a selective research process, mass-applying thru AI supported processes. 
• I can speculate for example that some enterprises could decide to make the first application process shorter having many hundreds or thousands applications received in just few hours or even minutes instead of days and the job automated application engines on the market would hype to identify and apply in realtime as one job would be on the market available with continuous opportunities monitoring, leaving all those people not using such engines, simply too slow to react to the market offers.
• Again here, I would believe some AI Agents could be the next level of automation of filtering and evaluation on both sides, from job application platforms and from hiring platforms. What is clear is that these are going to be more and more AI to AI interactions as I can see and each enterprise will have to find itself prepared to manage such type of process change.

On this section, I try this month only to remind that 

• in October went live the NIS2 regulations and seems that 34% EMEA companies didn’t plan according and shifted budget from other areas to the NIS2 activities.
• Finally, as last reflection of this month, looking to those figures, out of 34% of companies that missed a proper budget in the EMEA for NIS2, the budget was retrieved for 30% from recruitment meaning impacting either other areas to innovate either IT Ops. 

When I think that Cybersecurity is a well structured department from years in enterprises and can still struggle to get properly funded, it makes even more tangible my speculation of last month in the October newsletter when I was assuming that, if not properly set boundaries around deliverable, benefits, ROI and risks, AI will risk to take progressively budget from the IT Ops budget and other IT innovation initiatives budgets, impacting on the overall IT roadmap.