Category Archives: AI

It’s Not a Functional ExtAInction Battle in Procurement — But It is a Battle in the C-Suite (Part 2)

Namely, it’s a battle of propaganda versus reality, lies versus truth, against not only the other departments but the vendors selling solutions built on the lies and the consultancies coming in and spreading new lies on a daily basis!

The reality is that even though AI is NOT advancing at lightning speed, the claims around it are and that’s more dangerous than the tech. People are getting lured in to tech that’s not market ready, and that’s why so many projects are failing.

Even worse is the 5% that aren’t failing. Even though most of these are far from a resounding success, when the AI works good enough on the mostly tactical tasks it is installed for, the organizations start to trust it (even when they shouldn’t) and get overconfident on the ability of AI. These companies then approve a slew of AI projects and prematurely get rid of people they shouldn’t, hindering everyone’s ability to do a proper job. This can lead to Procurement extinction when it leads to organizational extinction with not enough people left to deal with the first crisis that materializes that the AI can’t handle.

Procurement has to find a way to win the battle of propaganda and stave off “AI” that is unproven or that is in select use cases the organization is not yet ready for due to a lack of data, systems integration, or knowledge to properly use the real AI that works. Otherwise, it won’t survive, and there’s a chance the business won’t either with one economic crisis after another; supply chains constantly breaking as a result of trade wars, sanctions, and border closings as a result of wars and geopolitical uprisings; demand constantly shifting as unemployment and costs rise; etc.

In other words, as the authors wrote in the Functional ExtAInction Battle white paper we started discussing yesterday, we are in an Age of Disruption, but it’s not the tech (which rarely works), but the marketing and lies around the tech (that all of the psychopathic CEOs want to believe so they can fire all their human workers and replace them with 24/7/365 robots that don’t have any rights and don’t need to eat or sleep). The sad thing is that we’d have a better chance of surviving an age of real AI than this, especially when lying is now sanctioned in the USA and instead of being investigated by the FTC you are given a free pass, and should a state court convict you, you can just buy a pardon! Given that most people didn’t understand technology before the Age of (Fake) AI, how can you expect to understand AI and what is real and what is not?

Moreover, an Age of Evolution has to follow because the C-Suite believes,
right or wrong, that every aspect of their organization has to digitally evolve or they will die. This means if that Procurement doesn’t evolve digitally, it will be replaced by a function, or a team, that does. Fortunately for Procurement, every vendor, and their office dog, now claims to be AI-backed, -driven, -enhanced, -first, -powered, etc. even if they don’t have any AI at all! This means that Procurement can select a solution that works for them, which uses configurable, adaptable, RPA; embeds best practice; encodes decision optimization and predictable, dependable trend analysis in its analytics; etc. and automates 80% of their work error free. They can evolve, look like they are meeting the impossible AI mandate, and get better results than the rest of the business.

Finally, a new world is coming because, once we have the AI crash, vendors with real solutions built on real, traditional, AI models that can now be effective with the data available and processing power at our disposal will emerge. Instead of searching for the magic model that will supernaturally become emergent and achieve intelligence and work on every problem, the next generation of vendors will take the time and make the effort to integrate dozens (if not hundreds) of traditional, appropriately trained, models that reliably solve point-based problems with high, and often near-perfect, accuracy; encode guardrails for the rare situations in which the models might fail; and build workflows that are easy to follow, execute, and even manipulate and that solve the tactical data collection, manipulation, analysis, and export problems that take up the majority of a Procurement professional’s time and deliver no value in return for their completion. Procurement teams that wait to identify and adopt this technology will be the ones that rule the new world, while the other teams (departments, and maybe even businesses) won’t exist any more.

Moreover, the Procurement professionals of tomorrow will be almost entirely focussed on strategic capabilities, as the need for tactical efforts will be rare and limited to not yet seen exceptions (as each resolution will train the platform which will then be able to handle similar exceptions reliably from that point on). This means that today’s Professionals need to start preparing for that eventually. They don’t need to rush, but they do need to start and make steady progress.

When we say the urgency is not as great as the authors make it out to be, we mean it. the doctor has been covering this space for 20 years. For 20 years he has been reading “future of” white papers that proclaimed the space was going to be totally different in 10 years. This means that the space should have been totally transformed by modern tech 10 years ago. Guess what? It wasn’t! Nor was it the next year. or the year after that. Or the year after that. For 10 years the predictions of radical transformation have failed to come true. While the pace of digitization will increase, the trend will continue to hold. After all, the point of Procurement has not changed since the first manual was published 138 years ago. The world may have changed, but the world’s second or fourth oldest profession has not! (Now, if the “sales” profession really was the oldest, that makes the “buying” profession the second oldest. However, before that we had [religious] leaders and stargazers, which are still professions today. So that would make “sales” the third oldest and “buying” the fourth oldest, despite the claims.)

We agree you have to start today, but you will only win the race if, like the tortoise, you go slow and steady and master each step while the others try to take shortcuts with tech they don’t understand, become overconfident in the great sounding (but incorrect) outputs that are returned, get lazy and lethargic as a result, and nap on the job — allowing you to pass them by.

Like objects in the rear view mirror, AGI appears closer than it is. (And that’s a good thing, because if AI actually emerges, we are not likely to continue on this planet.)

Like we said before, the paper is worth reading, it gets the stages right, it gets the mild urgency right, it just gets AI wrong (at least where it is today and will be tomorrow, and the day after that, and the day after that for quite a while … at least until entirely new models and breakthroughs are made that may actually model intelligence and not just random computation).

Plus, the history lessons (including those which really don’t have anything to do with Procurement, but it’s a nice lesson anyway) are a good read for those that didn’t study history in school (or even remember what happened last decade).

Is It a Functional ExtAInction Battle in Procurement? (Part 1)

About a month ago, Jonathan O’Brien of Positive Purchasing and Guy Strafford of OneSupplyPlanet released a white paper on this very topic where they claimed:

AI means Procurement is going to be left jostling with the rest of the business to control the commercial space. It is a race. Start now or lose.

I have to say I don’t agree. In fact, we’re still in the start now AND lose timeframe, as evidenced by the recent MIT study demonstrating that 95% of AI projects have failed and the plain and simple fact that the majority of consultancies, providers, and new-age services-as-software providers claiming to provide AI Employees (which is all bullcr@p by the way, see our previous posts as AI Employees Aren’t Real) are applying the wrong AI to the problems they believe AI can solve. (And that’s another issue, real AI can do quite a bit, but not what the greatest con-man since PT Barnum not in politics keeps telling us it can do.)

However, they’re close. You need to start learning what AI is and isn’t now, looking out for the past and next (NOT current) generation of providers who were applying real AI properly and who will emerge to apply next-gen implementations of real (non-LLM) AI properly to Procurement problems (with real education and real procurement experience to back it up, and that’s not a Youtube crash course in how to engineer a prompt for a bullcr@p LLM, by the way). That way, you can select the right solution for the right problem at the right time.

You are going to have to jostle with the rest of the business, especially Supply Chain who believes they are the most critical function (when they are only one side of the critical coin with Procurement being the other half), IT who believes they have the best technical knowledge and should make the decision (and don’t really understand what the tech has to do for the rest of the business, just what is easy for them to maintain and fun for them to play with), Finance who wants to ensure they have better visibility and control over every dollar, Sales and Marketing who want to pretend the age of the Mad Men never ended, and so on.

Moreover, while many of the activities carried out by Procurement functions will be automated, these are just the data entry, transformation, and output functions that we were promised would be automated 40 years ago when computers started entering the average business. We’re not going to see the automation of the strategic functions, the relationship management, or the consensus building that is critical to success. While the authors may claim that many Procurement activities will soon be managed directly by the business, that will be a step back as we’ve seen, and Hackett has catalogued, the significant difference in performance in businesses that have standalone best-in-class Procurement departments and those that don’t have any Procurement departments. The reality is that, in the economic and technological climate that is coming, businesses without Procurement likely don’t have the same chance of survival as businesses with Procurement.

According to the authors, all that will remain are the commercial hub activities that require human expertise and intervention: change management, innovation, and sophisticated market engagement. While these will definitely remain, the reality is that you can’t turn supplier discovery, qualification, onboarding, relationships, performance management, development, and innovation over to a machine. You can’t build organizational consensus through emotionless algorithms. Not all award decisions can come down to the results of lowest cost computations after automated negotiations based on bid rank or classic game theory (or even modern game theory as many of the game theory “experts” get this wrong regularly, as the author has poked holes in claimed “optimal” solutions presented on LinkedIn and vendor websites more than once, because there’s always an assumption as to what optimal is, and it’s usually one sided or wrong). Technology will reduce the time requirements for a lot of these processes as it will fully automate the data collection, transformation, analysis, and recommendations for you, as a human expert, to one-click accept or deny, but a human will still be needed. All that will disappear is the 80% to 90% of the work that is tactical data processing. While this will displace people, as all technological evolutions do, we need to remember that each evolution has ultimately resulted in the creation of new jobs as old ones get automated. Not only will people be needed to maintain the automations and hardware supporting them, but new strategic and creative jobs, some of which we can’t yet predict, will emerge as a result.

Moreover, the authors believe that since such capabilities are found across the business, the other functions … will want to move into this commercial space and that unless Procurement develops the skill sets to a higher standard than the other functions, it will be outpaced.

While they are not wrong, and while this will make life difficult for Procurement if other functions get ahead of them in terms of value delivery to the business, Procurement is more than just change management, innovation, and market engagement. However, without this core, Procurement’s differentiation will be limited and its overall influence over the business not what it should be.

Moreover, while there will be a battle to evolve and survive post AI, we’re not there yet because what we have now is not AI, it’s the latest instantiation of Silicon Snake Oil with grandiose, false, claims and no real value. We’re still a few years away from widespread application of real, useful, AI, and more than a few years away from post-AI. In other words, the likelihood of Procurement being phased out as-is by 2035, as the author’s claim, is not too likely at this point. However, depending on how fast we get to, and through, the Fake AI crash and on to real AI, Procurement could be in deep trouble in the early 2040s. Which is why you have to start learning about real AI today, where you can apply it safely and effectively, and how you can implement it bit by bit for stable, guaranteed, success. Learning — not rushing in to an incomplete, half baked, solution guaranteed to make you the next casualty among the 95% error rate — is key.

So for those of you who asked, that’s my initial response as to whether or not there is a Functional ExtAInction Battle in Procurement. There’s the same battle there’s always been, but without real AI, and without the rest of the business having the deep Procurement knowledge necessary for real Procurement success (which goes well beyond what can be automated today), there’s no chance of ExtAInction in any Procurement department which is a leader in its operation.

However, even though the conclusion is wrong, the majority of the observations and analysis in the paper is right. In fact, it’s one of the best the doctor has read yet in terms of analysis and insight. So in our next post(s) we are going to discuss that. Despite a few mistaken conclusions, which can be forgiven because it’s really hard to understand the reality when it takes a very advanced understanding of mathematics to understand the tech, which is necessary to understand the reality, it does a great job of figuring out how Procurement needs to be seen and why. So download the white paper and read it today for the insights within (without having to worry about an extinction that won’t happen … at least not yet).

ChatGPT is NOT Your Friend!

I’m still seeing too many posts out there on how ChatGPT is your friend and how it’s the biggest productivity hack ever and this has to stop.

It’s Not Your Friend. It doesn’t care if you live or die and will not only urge you to give into any and all suicidal thoughts, but provide how-to guides for you.

It’s not a productivity hack, because it’s, at best, a drunken plagiarist intern and you have to review everything it produces. Moreover, you have no clue if it’s mostly right, partially right, or a complete work of fiction. I was reminded of this the other day talking to a tech guru on a legal team that asked their LLM about what laws might impact a new contract with a new supply chain setup in the affected regions, and the LLM came back with three laws, complete with full text and author/site citations, that the team should review for relevance. Upon digging into each law, they found that none of the laws were real, and everything was completely fabricated — the laws, the citations, and sometimes even the bios/bodies who supposedly wrote them! It didn’t matter how much careful prompting they gave it, how specific the request was, and how much time went into building the request and allowing the LLM to do its thing, at the end of the day, it still made everything up and wasted a few days of the team’s time — forcing them to start from square one the old fashioned way and do it all over.

This is why, despite every consultant’s claim to the contrary, ChatGPT CAN NOT create a good draft of an RFP simply from a template and a product or service identification. In the best case, all it can do is just repeat the suckage found in the majority of RFPs in the data set it has been found on. If there weren’t enough RFPs to train its probabilistic predictors, it’s going to make stuff up that, unfortunately, sounds really good because the models, for the first time, capture the intricacies of putting words together to not only form proper linguistic utterances but do so in the common vernacular, which means it sounds human, smart, and right when its still a machine, dumb, and wrong. And no matter how good the “reasoning” seems to be, it won’t be based on logic and will be wrong and circular, but it will take more deftness and effort to catch the mistake than just write your own RFP from scratch. (Now, this doesn’t mean that SLMs can’t be trained to help you in RFP construction and reduce your workload 80% to 90% of the time, just that LLMs can’t be used and even with SLMs, a human will still need to be heavily involved in the process and review. However, to date, I’ve only seen ONE company get this right so far, and have only talked to two or three more that are on the right track.)

I tried to address this in my Best Practice Tech Selection reprise, my How to Write a Good RFP, and my Bells and Whistles Lead to Cells and Thistles series, but apparently I’m not clear enough as the LinkedIn influencers and the consultants and analysts they are influencing still aren’t getting it!

ChatGPT can’t do your work because it is NOT intelligent. All you are accomplishing is dirtying our atmosphere and denying our fellow humans clean water so that you can power queries (and keep the machines from overheating) that take 20 times (or more) the processing power of a Google Search and aren’t guaranteed to return any usable results (while allowing your cognitive abilities to atrophy through over-reliance on dumb tools). (We should not see stories about how I Can’t Drink the Water in the richest and most powerful nation in the world [because of a data centre]! It’s shameful! But we are now seeing these stories, along with “I don’t have water!” stories because data centers are now consuming over a trillion gallons of freshwater globally, a resource we are running dangerously low on in many countries. Half of the USA is already suffering from water scarcity issues! And you’re literally making it 20 times worse thanks to your ChatGPT addiction!)

For an RFP, it’s not a high level bill of materials, feature / function / support checklist, or detailed profiles of what you think you need — it’s processes you need to support, capability gaps you are missing, and skills that you need augmented. ChatGPT, or any LLM doesn’t know that! Only YOU know that. For many other tasks that require human intelligence to figure out, it’s the same story — ChatGPT doesn’t know, makes stuff up, and gives you suckage.

Moreover, you can’t trust it for deep data analysis. It has been demonstrated to get basic math wrong many times (or, when pushed to find savings, multiply a result by -1 and lie to you). It can usually compute directionally accurate results, but that’s it. But we’ve also seen many instances where the EXACT SAME QUERY was asked twice in a row on a data set that did not change, and it gave two different answers. Even the dumbest drunken plagiarist intern would say “I just told you the answer you nitwit. It’s this!” Moreover, right or wrong, the dumbest drunken plagiarist intern would repeat the same answer. (It’s so bad that even Gartner has projected that conversational analyticswill fall off of its hype cycle within 2 years!)

Furthermore, it is not intelligent, and has no brain, so it cannot brainstorm … the best it can do is serve up other people’s ideas you may not have heard about! There’s a reason you will not have thought of some of the ideas it brings back, and the reaason is the ideas it will bring back are so ridiculously stupid (and obviously wrong) that only a complete and utter moron would give them a second thought.

It’s a fun, planet destroying, toy that will always hallucinate, because that’s part of its core design, and that may or may not give you something useful on any given query. So if you have to manually verify everything it does, how can it be worth using?

And yes, it really does destroy the planet compared to classic Google Searches. This YouTuber does a great job of explaining, in plain English, How AI is Impacting the Planet for those of you who refuse to process the written word I keep presenting to you.

But if you don’t mind planet killing, or a technology tool that will expose your entire conversation history and confidential/trademarked/top-secret corporate data to the whole internet, then be my guest and use it. It’s your business. Feel free to flush it down the toilet if you like. Not my place to tell you not to.

I’m just here to remind you that ChatGPT is NOT your friend! (And neither is any open LLM!)

GEN-AI is Failing 95% of the time. What does this mean for you?

We’ve known for a while that

  • Gartner’s first study found 85% of AI projects were failing (and that statistic is still being quoted everywhere, including this recent Medium Study)
  • Bain’s study last year found that 88% of all IT / technology projects fail to some extent (2024 study)

And we now know, thanks to MIT, that

  • 95% of all Gen-AI pilots fail. (Source: Fortune)

So what does this mean for you (and your ProcureTech journey)?

Well, beyond the obvious that you should stop dead in your tracks when a vendor starts pushing their “Gen-AI” enabled solution and dig deep into what that really means, at a foundation it means that:

You should never, ever, ever buy or use any solution that uses third party Gen-AI / LLMs, even if wrapped nicely, in their service or product because your chance of success will be 5% if you go with that provider.

You should only select vendors who only use in-house Gen-AI / LLM solutions that are built with the following rules in mind:

  1. custom trained on an expert culled corpus
  2. for a specific problem domain
  3. and applied in a specific context with guardrails and human checks on the output.

The best AI technologies has always been focussed on a specific problem, and this iteration is no different. Focus minimizes the LLM hallucinations (which cannot be trained out as they are a fundamental function of the technology) and guardrails prevent them from automatically being executed on / slipping through.

While they are far from perfect, with more discoveries being made daily on their many (many) drawbacks (where we summarized a dozen in this post on what not to do if you got a headache, but missed the recent revelation where it can not only lie on purpose but turn into something evil), the reality is that, as we have said before, LLMs, properly trained on vetted corpuses, do have two valid uses:

  • large corpus search and summarization
  • natural language translation

since, when appropriately trained, they can be almost as accurate as last generation semantic technology systems, but provide much more natural interfaces for the average user. (However, you won’t get a failure code from them when they are wrong, you will get a hallucination which will be so well phrased you’ll think it’s true when it’s an outright lie. Hence the need for guardrails and human review.)

So, if the vendor is

  • using their own in-house LLM
  • following the rules above
  • and targeting the LLM at natural language problems LLMs are actually good for

Then you should definitely try what the vendor is selling. (Try, not buy, and definitely don’t make a decision off of the carefully crafted demo!) Put it through its paces in a typical use-case for your company, not the use case selected by their demo master. If it does the task better on average than an average team member or does it about as good but many times faster, that is what you are looking for in a tool. Since there is no real AI, you can’t be replaced. But as your bosses keep increasing the weight of your workload to hit ridiculous revenue and profit targets, you need a tool that multiplies your productivity. One that can do the majority of the tactical data processing grunt work, leaving you free to do the strategic thinking and then add in the intelligence to a process or output that no tool can possess, instead of spending 90% of your time doing data entry, processing, and summarization that computers were built for.

In something like Procurement intake, that’s not trying to mimic in text chat the old school phone conversation that took you fifteen minutes to do the monthly office supplies re-order, that’s asking one question:

What do you want to do today?

processing the first one sentence answer:

Place the monthly office supplies re-order.

to determine that the user needs to be pushed into the e-Procurement system with the monthly office supply cart pre-loaded, so that all he has to do is enter the number of units of each item, and possibly add or remove an item from an easily searched catalog if one or two items need to be changed. Not 20 questions of “what do you need”, “what quantity”, “the same supplier”, “so you want 2 cases of paper from office depot”, “no, office max”, “oh, standard printer not glossy for marketing”, etc.

When Gen-AI mania first swept our space, and every vendor was told they needed a conversational interface for buying (or no customer would consider them in their RFP), and then built one, not a single one wasn’t painful to use. Most customers upon seeing it for the first time (after insisting on it), quickly said “can we turn it off” because they quickly realized that a well designed catalog with blanket/standard orders, quick search, and easy drill down to preferred suppliers was at least 10 times faster than trying to use a dumb chatbot — especially if they could pre-build templates / carts / blanket orders for regular purchases.

It’s the same for almost every other process vendors have been trying to apply this technology to, including conversational analytics. (Which, FYI, even Gartner expects to disappear from the conversation in two years.) There’s no such thing as conversational analytics, only reporting. And while that is really useful in the right context (such as allowing an executive to retrieve some basic information with a plain English question), try building a detailed spend cube, which is the cornerstone of spend analytics, with conversational analytics! (And I mean try because you will fail.)

While this doesn’t mean that LLM technology doesn’t have uses, it does mean that those uses have to be finely tuned. So far, among the hundreds of companies I’ve seen over the past few years, only a few have both implemented LLMs and gotten it right. Let’s hope that number increases in the near future. If, not always remember, while it would be great if a few more companies would get it right, You Don’t Need Gen-AI to Revolutionize Procurement and Supply Chain Management — Classic Analytics, Optimization, and Machine Learning that You Have Been Ignoring for Two Decades Will Do Just Fine. Not to mention the fact that good, adaptive, RPA will take care of most of your automation needs!

Why You Should NOT Engage Any Vendor Selling “AI Employees”!

It’s not just complete and utter bullcr@p, but it spreads a dangerous myth while demeaning and degrading all of us!

Complete and Utter Bullcr@p

As per AI Employees Aren’t Real! Don’t Believe The Lunacy:

  1. There is no Artificial Intelligence.
  2. An Employee is a Person!
  3. Fully Autonomous Software Agents Don’t Work.

Nor will they ever work with current technology as the existing algorithms, stacks, and technologies are not emergent, as has been proven, nor will they ever become magically emergent.

A Dangerous Myth

Psychopathic CEOs have been investing in technology for years with the dream of replacing employees who need fair wages, benefits, reasonable working hours, safe working conditions, and other costly annoyances with technology that can work 24/7/365 without any breaks, rights, or complaints. Given that each evolution of technology has enabled whole new categories of data processing and analytics jobs to be mostly automated, they have convinced themselves they will reach their technotopia in their lifetime where they can replace almost all their office workers with AI. For the past few years, they have heard the increasingly ridiculous claims of the Gen-AI vendors that “with just a few more trillion for dedicated data center construction and bigger model development, AI will achieve emergence and be able to do the work of a PhD level human” and have been waiting for that day.

Now you have vendors falsely claiming we have reached that day, and that, for less than the cost of an employee (or team), they can layoff entire departments and replace those employees with their custom Agentic AI that will do everything the employees did, flawlessly, 24/7/365, with the ability to scale up and take on more workload as needed.

But nothing is further from the truth. For example, this tech:

  • can only be encoded/trained to handle known situations with appropriate responses; when an exceptional circumstance arises that is not in the encoding/training data, it won’t know what to do;
  • is not flawless if any part of it is based on (Deep) Neural Networks or Large Language Models; the former will have a maximum accuracy rate and the latter will be completely unpredictable as you can ask it the same query five times in a row and get five completely different responses and there is no way this can ever be trained out (it’s another fundamental property of these systems, as per recent research); and
  • only works well on tasks that are computationally oriented, not on tasks that are more emotionally oriented.

They are making false promises that is not only giving companies an excuse for mass layoffs, but an incentive for mass layoffs that will not only harm you (as you will be unemployed), but harm them and their relationships (when the tech pays a fraudulent mulit-million dollar invoice, allows safety checks to be bypassed, and replaces a long-term proven supplier with a cheaper imitator whose only goal is to extort as much as it can from the market before suddenly declaring bankruptcy due to CXO embezzlement).

Demeaning and Degrading

Even if you could swallow all of the lies by saying “it’s just marketing“, you shouldn’t because it is demeaning and degrading to all of us to equate a piece of software with an intelligent human and claim one can fully replace the other.

There is absolutely no question that a machine can compute better than we can. They were designed to be the ultimate computational machines that could flawlessly perform trillions of calculations per second, and that’s what they do.

There is absolutely no question that the machine can do certain tactical data processing and analytical tasks way better than we can or that they should be employed to do so. Moreover, the tech that allows them to do these tasks has existed for at least a decade, if not two, and workforce displacement was inevitable. However, displacement does not mean elimination, it means shifting towards more strategic, relationship, or manual tasks that computation cannot capture.

Accounts Payable departments were doomed to shrink (as we had invoice processing solutions almost 10 years ago that could, with the right effort, increase straight through processing rates to 90% or even 95%), statistical analysis and data reconfiguration departments were doomed to go the way of the Dodo (because the vast majority can be automated and what can’t can be consumed by the departmental analysts that need to do the analysis), and the need for Procurement Buyers was doomed to be minimized as time progressed (because you can automate catalog orders, standard RFQs, inventory replenishment, etc.).

But claiming that tactical computation can take over strategic reasoning, which “AI” cannot do because it’s not strategic (although it can compute inputs to well-defined models); that cold computation can replace warm relationships; and that dumb probabilistic mush can replace human intelligence is demeaning. Furthermore, pretending that you can replace a valuable human employee with a costly piece of dumb software is degrading. (It is considerably more costly than you think. See Joël Collin-Demers post on The Dirty Little Secret Behind Gen-AI Functionality Pricing on why these vendors are switching to outcome pricing, and the reason is to hide how costly this technology is relative to the return.)

Succinctly put, you shouldn’t put up with it. You deserve respect, and that is something that vendors claiming “AI Employees” are taking away from you!

This why Sourcing Innovation had to update it’s Product Review Requirements for the first time since posting them back in 2007! While it has no problem with Agentic AI (as long as it’s just enhanced RPA which we know works), and can even deal with Agentic Workforce (since it is doing a form of work), it cannot accept AI Employee and is drawing the line here because someone has to!

This is why, after 18 years, SI had to include as part of product review requirements that the vendor accepts that SI has a no Bullshit policy, which includes no (Gen-)AI Bullshit, and SI will NOT cover you if you make ridiculous or false claims (that are not backed up by live demos and/or case studies with a customer that will go on record); this includes, but is not limited to, claims of AI Employees that we have already debunked. It’s not going to peddle your panacea poison!