AI, Value Creation and the Future of Business: Why Automation Is Only the Beginning

[00:00:00] - [Speaker 0]
The leading issue of agentic AI in businesses right now is ensuring agents act with compliance guidelines, and Denodo applies guardrails across your entire data estate. By aligning your company's data infrastructure under one system, these guardrails perform consistently across your platform. So start scaling your business and start with Denodo. Simply visit denodo.com to learn more. What if the biggest mistake businesses are making with AI is using it to automate work that shouldn't exist in the first place?

[00:00:39] - [Speaker 0]
And my guest today is the cofounder of a company called Blue Chip, and she believes that companies that win won't be the ones using the most AI. They'll be the ones willing to rethink how their business is creating value. So today, we'll discuss why nobody wants to pay $300,000 for a slide deck that they can create in AI in a couple of minutes, and why human attention could become a luxury service, and why putting AI on top of messy data and broken processes is nothing more than a expensive way to create chaos. But I don't wanna reveal any spoilers now, so let me introduce you to my guest. So thank you for joining me on the show today.

[00:01:22] - [Speaker 0]
Can you tell everyone listening a little about who you are and what you do?

[00:01:26] - [Speaker 1]
Sure. So my name is Joanna. I'm CEO of BlueClip. BlueClip is an AI company that is supporting supply chains to automate their processes with AI. But before I started BlueChip, I actually I used to work for Ernst and Young, so one of the big four companies in their supply chain practice across Europe, Asia, US.

[00:01:48] - [Speaker 1]
So now I'm based in The US. After several years with Ernst and Young, so I think I was with them for fifteen years, I decided to leave and I joined Marzurigi snacking company. So all those like snicker snicker bars, Twix, pet food, where I was also supporting supply chain digital transformation globally for more strictly. And this is where BlueClip was born from my struggles at work. So today, I'm I'm trying to help companies, you know, optimize their supply chain with AI solutions, but in a very responsible way.

[00:02:23] - [Speaker 1]
And we'll probably talk a little bit more about this later.

[00:02:26] - [Speaker 0]
Yeah. So I'm looking forward to talking about that with you. And one of the things I love doing on this podcast is busting a few myths and misconceptions, and that is one of the many reasons why I was excited to get you on today because we've looked at our news feeds. When people talk about AI, they typically jump straight into, well, it can save you time, but you push back on this. You say the real shift is about cost, not speed.

[00:02:51] - [Speaker 0]
So what's actually getting cheaper here, and and why does that matter more than just another productivity story?

[00:02:58] - [Speaker 1]
Oh, this is an amazing question. So, of course, AI is going to help us with productivity. So don't get me wrong here, because AI can automate many things, provided that we implement AI in a responsible way. If we do not do this, AI can create lots of chaos. But for me, productivity is just a small piece.

[00:03:19] - [Speaker 1]
The biggest change is around value. So throughout the years, companies were creating their value on, you know, analysis, data, knowledge. With AI, now everything is accessible. You can run analysis very quickly. You can do your research very quickly.

[00:03:38] - [Speaker 1]
You can constantly analyze your data. You have access to lots of knowledge that is on Internet. So now this this knowledge is actually cheap. So this is what is changing because in my opinion, the value that companies are creating today, it's changing. And the impact will be different depending on the type of company.

[00:03:56] - [Speaker 1]
So let's take manufacturing companies. They have product, so they have r and d. So the impact will be probably slightly smaller for them, although knowledge also plays a significant role. So creating ideas, it's not really the most important thing. But then let's take consulting or service companies.

[00:04:16] - [Speaker 1]
Their whole business is just a is just on knowledge. So how they analyze things, how they deliver this knowledge. And this is something where I think the value will be shifting. Because nobody wants to buy today like a slide deck for 300,000 US dollars that we used to buy. I was the one who was providing those slide decks.

[00:04:38] - [Speaker 1]
And you know, when I was at Mars, I didn't like those slides. It's because for me, it's like I'm getting beautiful sheet of paper with beautiful slides, beautiful pictures, but I know that with Claude, I can generate the same content in two hours probably, and my license will be $200 a month, not 3 So 100 so this is a change. And, you know, that is why value is changing because people will start, I think, buying different things and buying differently. They won't be really interested in buying knowledge. They will be interested in buying outcome and result.

[00:05:14] - [Speaker 1]
Because nowadays, like, you do not want the slide deck. You want implementation. You want to see the results. You want to see, you know, this impact on your p and l. So everything will be will be changing.

[00:05:25] - [Speaker 1]
That is why I'm saying AI, it's not only about productivity. It helps with productivity. But AI will completely transform how people are selling and buying. So it transforms value, that companies are are delivering and are buying, in my opinion.

[00:05:42] - [Speaker 0]
I love this value, outcomes, results, and after years of AI hype and noise, it's so refreshing to hear you talk about this. And I've got to ask though. I mean, if the cost of research, analysis, and reporting is ultimately heading towards zero or a much more affordable rate, $200 versus $300,000, for example, that you mentioned there, what what is that thing that customers will still happily pay a premium for?

[00:06:10] - [Speaker 1]
Unique knowledge. So so this is this is something that I think will be still available. So customers won't be really willing to pay for knowledge that is easily available on Internet. Everything that is within AI, it comes from Internet. But on top of this knowledge that is on Internet that you can search, there is knowledge that you can not find there.

[00:06:33] - [Speaker 1]
That is coming from your practical experience because someone was on the floor. They saw mistakes happening. They know that in this business, those are the typical mistakes. Those are the things that you should usually look for. And and this is something that people will be willing to pay.

[00:06:49] - [Speaker 1]
So practical experience, benchmarks. This is another thing that I know for my clients when I was at was very difficult to acquire. There are just few companies that are gathering this data because this is, you know, confidential information. So to get information and validate, okay, is my process efficient? Do I have enough benchmarking analysis to compare how I'm performing against market?

[00:07:14] - [Speaker 1]
To see it's like, you know, whether I need to make some changes. This is, I would say, third area of the knowledge that that companies will keep buying. Then, of course, as I said, outcomes. So implementation, making sure that they are able to deliver. And the interesting point and, you know, probably many people won't agree with me, but I think that we will be buying actually human touch.

[00:07:37] - [Speaker 1]
Because nowadays, from my perspective, I believe that human human touch is becoming a luxury. So I'm not sure if you are feeling the same thing, but you know, for me, I'm overwhelmed with cold messages. All like vendors trying to sell me something. All those messages look the same. And I know it takes me like one second to spot a message that was written by AI.

[00:08:01] - [Speaker 1]
And I think that with all this noise that AI is creating, human touch is actually getting more valuable. But of course, this needs to be, you know, high value adding activity from human, not something that can be really really automated. But I feel that this human touch in terms of like sales, customer service, this will be a premium service that that companies will also want to buy. At least, I want to buy this because I'm overwhelmed with with all the hype on the market and everything that AI is putting on me.

[00:08:33] - [Speaker 0]
Again, completely agree with you. I think if anybody scrolls down their LinkedIn news feed at the moment, they will see fifty, hundred different, statuses and updates that all look remarkably the same.

[00:08:45] - [Speaker 1]
Everything sounds the same. Right?

[00:08:47] - [Speaker 0]
Yeah. Yeah. It's the same thing.

[00:08:48] - [Speaker 1]
Everything you read this and everything sounds the same. And this is the problem. And, you know, all those, like, constructions, it's not that, but it's that. And and, you know, you know or, like, what is else? Uncomfortable truth.

[00:09:01] - [Speaker 1]
Oh, I love this. Every second post you see this on LinkedIn. And and that's why I feel like being real, this will start creating value. And, you know, with AI, people started saying, copywriters, they will lose their jobs. Marketing people, they will lose their job.

[00:09:18] - [Speaker 1]
I don't think so. They will be actually more expensive because they will be able to create something that will be different. Because AI is putting everyone on the same level. Like, they're bringing everyone to be very average. So how to be different in this world?

[00:09:34] - [Speaker 1]
I think it's human touch to help Yeah. To help us all be be different and and sound better.

[00:09:41] - [Speaker 0]
And I think it's the same in corporate America and all large organizations as well. A lot of business leaders, they cannot help themselves and seem to have this legacy mindset that they cannot shake off. So if they hear any new tech story or AI in particular, they just think automate a few tests, cut some costs. But when I was doing a little research on you, I was reading how you say that the spat is actually the smallest part of the story. So if automation is just that small first step, what's the the bigger prize that they're missing here in your opinion?

[00:10:13] - [Speaker 1]
Transformation. I really love this world words. So, you know, AI helps us not only automate, but I think that with everything that I said in terms of, like, value creation, AI will help companies transform their businesses. How they create value, how they deliver value. And from my perspective, I believe that with all this hype and everything, companies really need to start making some bold decisions around reviewing how they operate, what can be changed because AI will be more more intelligent, will get more knowledge.

[00:10:53] - [Speaker 1]
So with time, I think that the value of knowledge and cognitive work will start dropping. So companies need to start transforming their businesses around AI automation and really start to think about what is unique. So this is one area. Second area from my perspective is continuous improvement. So we always had those teams that were doing analysis, research, blah blah blah, but this was not continuous.

[00:11:23] - [Speaker 1]
This was just their title, continuous, but those analysis took time. And and, you know, whenever you had all those results, in my opinion, very often those results were outdated because business was moving, market was moving. So now we have this real opportunity to have through continuous improvement and actually, evolving their business continuously as the market is changing. Everything will be quicker. Market will be changing more quickly, and companies will also need to change more quickly.

[00:11:55] - [Speaker 1]
So that is why I'm saying it's not automation. Automation is peace. It's a way bigger picture around transformation and making sure that we design our organizations to be agile in a way that we can catch up with everything that is going on on the market and make sure that we are not left behind. Because this will be a big problem and and I think that those companies that are able to implement and use AI more holistically, not just to automate their back office activities, but redesign the operations to be in some areas a native, those will survive on the market in the future.

[00:12:34] - [Speaker 0]
And what I love about your stories, you've had a front row seat of how things used to be done and now playing a very active role in how things are evolving now. I mean, you've spent years in consulting before founding Blue Chip, so you've watched this evolve from the inside. And and when the analysis a client used to pay weeks for can now be done in minutes, what does a client look for in a consultant now when they're them? What are they looking for? What kind of help?

[00:12:59] - [Speaker 0]
And and how do you see this?

[00:13:02] - [Speaker 1]
Oh, very good question. So as I told you, it's like, in terms of those slide decks, clients can generate those in Clot. What they are interested in is practical knowledge that they cannot find in Clot. This is one area, but also later implementation and outcome. So now you cannot sell the project for $300 just to, you know, give me a slide deck and then team needs to take it, produce it.

[00:13:28] - [Speaker 1]
So so they are more interested in outcome. They do not want to pay for analysis. Because in the past, consultants were spending weeks, sometimes months, to analyze the data and then produce this beautiful deck. Clients didn't want to pay for this analysis, but they had to, unfortunately. So now this is something that, you know, it's changing.

[00:13:49] - [Speaker 1]
They want outcome. They want results. They do not want to pay for information and analysis. So that is why I feel that the consulting world will need to change significantly. And this was also a reason why I decided to leave consulting.

[00:14:04] - [Speaker 1]
Because I strongly believe that consulting will not die, but I feel that a specific type of consulting companies will survive on the market and those are those companies that are very specialized. Where you have people who were on the floor, who felt the pain, and they understand when something can go wrong. With general consultants, I think that very often their scope will change to be perceived more as insurance company, where sometimes when you are making the bold decision, you need someone to sign off on this to share the risk. Most probably this is how we are going to use those general consulting companies, to share the risk and have them as, you know, some sort of insurance in case we we do not want to be fully responsible and accountable for all those decisions. But I feel that consulting world needs to evolve and be really practical.

[00:14:59] - [Speaker 1]
And another thing that is important from my perspective, I feel that also pricings, pricing within the consulting will be cheap. So in the past, customers were paying hourly rates or retainers for consulting companies, I think it's gone. I think that what clients are expecting now is more success fee, maybe gain share, not really hourly fees because they want to pay for real value that is being created that cannot be created by AI. And I can tell you, a lot can be created with AI if you are using it in the right way.

[00:15:34] - [Speaker 0]
And we will have many listeners from companies that are pouring millions into AI collectively. They're putting billions in there, and many say that they're still not seeing value from their AI projects. And I'm curious from what you've seen, what is it that's separating the ones that's getting those real results, those value and outcomes from the ones that are just spending more money?

[00:15:57] - [Speaker 1]
Yes. This is a very good point because I think this was MIT who said that ninety five percent of pilots in AI area fail. And I will tell you that I feel that they are starting in the wrong place. Because in my opinion, if you put AI on messy data, do not give context to AI. AI will hallucinate, and it will create a way more chaos for companies.

[00:16:21] - [Speaker 1]
So this would be overwhelming, and then AI pilot will fail. Where companies should start, in my opinion, it's foundation. Start with data. Prepare your data to be AI ready. Document your processes.

[00:16:34] - [Speaker 1]
Document your industrial knowledge. Something that cannot be figured out from your system. You have some rules. Put it on paper, and use it to train your AI. Build your knowledge layer on which AI can live.

[00:16:48] - [Speaker 1]
And then choose use cases. And this is another area where I see companies are choosing wrong use cases. Because everyone now is focused on ROI. But usually, those use cases with high ROI are not ready for AI. Because we do not have data, we do not have documentation.

[00:17:04] - [Speaker 1]
So CFO is signing off on this, and then he needs to actually write off the money for the pilot because it did not deliver. And the reason it did not deliver is not because of AI. It's because data was not ready. Your processes were not ready. So my recommendation for everyone is, first of all, Secondly, start in the right place.

[00:17:25] - [Speaker 1]
Making sure that your data is being prepared, you have the right documentation, processes, and then just use cases, maybe not sexy ones, but those where the data is ready. Start one by one. Not everything at the same time. Because I know that companies are selling many many companies, you know, vendors are selling end to end supply chain. Self healing supply chain.

[00:17:50] - [Speaker 1]
This is end goal for companies, not the start, in my opinion.

[00:17:55] - [Speaker 0]
Fantastic advice. And I I suspect that once AI can analyze and even recommend or when Leaders Discovery can do that, their next tempting move will be, hey. Let's let it decide. So I've got to ask, where do you draw the line? What should AI decide, and what has to stay with people?

[00:18:16] - [Speaker 1]
Yeah. That's a very good question. So I believe in human envelope and the journey. Because for me, it's like out of the box AI is like an intern. Does not have context, should not needs to be supervised.

[00:18:34] - [Speaker 1]
This is how I would say this. Then, so so you always start with human in the loop, validating what AI is doing. As this AI is growing and learning, sometimes you should be able to put AI on auto pilot for some selected use cases. Usually simple and repetitive ones, while you are still keeping human in the loop for more material use cases. And with time, the the number of those use cases on which you are able put AI, you know, to act on its own will be growing, but I still feel that human in the loop will always stay.

[00:19:13] - [Speaker 1]
Not only for those more material use cases, edge cases, but also to validate. Because, of course, we can do the tooling, we can ground AI in context, but still you cannot fully eliminate hallucination. The risk of hallucination always stays. And the biggest question from my end is, who is going to be responsible if AI makes a mistake? That is why you need this human in the loop, because c suits level wouldn't ever agree to be responsible for all the decisions AI is doing.

[00:19:47] - [Speaker 1]
They will need to have someone who is accountable. So I feel that the role of the human in the loop will be changing from, like, you know, training AI, guiding it, to supervising and being accountable for AI decisions, plus supervising at the same time those edge cases, more difficult decisions. And we we are not able, in my opinion, to get to a fully autonomous self healing supply chain because they feel that this human will always be important. Because you will always have some nuances, and nobody will agree to, you know, put AI on autopilot on your, like, most material clients, most material decisions if you know that there is even slight risk of hallucination.

[00:20:31] - [Speaker 0]
Yeah. Accountability is so important, and I love to have a bit of fun with you now. If there's a Fortune five hundred CEO listening to our conversation, or maybe they call you Monday morning and say, let's hope. Let's see what can make make that happen in a moment. But where if they ask you, where do I start with AI?

[00:20:52] - [Speaker 0]
What's the the first question that you have them ask themselves before just giving them an answer? What would you say to that person?

[00:21:00] - [Speaker 1]
First of all, I would tell them, just start. It does not need to be perfect, but just start. Because in my opinion, you know, it takes a lot of time to do this foundational work. If you wait, you will be behind all those companies that started. And probably you heard about AstraZeneca.

[00:21:17] - [Speaker 1]
So they announced some time ago self cleaning supply chain, but it does not mean they are there. What they did, it just they started. They started. This is their end goal, and now they are preparing them themselves. So they are doing this foundational work.

[00:21:32] - [Speaker 1]
Data, processes, all those things to get at the end at the end to this, you know, self healing supply chain. And this is, I think, the journey that every CEO, CFO from Fortune 500 company should have in mind. Start and start right with foundations. Data. Make sure that your data is ready.

[00:21:54] - [Speaker 1]
Validate how your data is being prepared. Enrich your data for AI. Document your processes. It takes lots of time to have your data and processes AI ready. Build this company brain that you can later feed into AI.

[00:22:09] - [Speaker 1]
Because putting AI on top of everything, it's easy. Documenting and building those workflows in AI, back capabilities, it's easy. Most time is always spent on organizing everything that you have to make sure that AI can reason and give you real value, not create chaos. So this will be my recommendation. And when you are ready to to start, think about your use cases, and do not think about glamorous use cases.

[00:22:36] - [Speaker 1]
Think about processes that are very repetitive, where the outcome can be can can it can be predicted. Not something that is, you know, high ROI, creates probably lots of value, maybe less less risky processes, where you can train your AI and test. And then you will start building your journey to get to the self healing supply chain, but it won't happen overnight, unfortunately.

[00:23:03] - [Speaker 0]
I love that. Great advice. Just get started. I always say version one is always better than version none. But if if I was to ask you to look into the future here, to the moments where the AI noise is at a much lower volume and the dust is starting to settle, What do you think will separate the companies that created that real value with AI from the ones that just kept pouring more and more money into it thinking that was the answer?

[00:23:26] - [Speaker 1]
Yeah. So I don't think that, you know, the the most successful companies will be the ones who are using the most AI. Probably not. The most successful companies will be those companies that decided to do transformation around AI, and decided to make this effort to change their business, how their business works, and how their business is creating value. They they do this difficult work organizing data.

[00:23:55] - [Speaker 1]
Will say it one more time because I already believe in this. You know, organize data, organize processes, go one by one, and also redefine how you deliver value. Because I I don't think that the future is in putting k I on your current processes, then you are just automating some broken processes, something that might be inefficient. First of all, get rid of those inefficient processes. Automate this with AI.

[00:24:21] - [Speaker 1]
Put people where the real value is, where they can create something creative. Something something that is very unique. And this is this is this is what will distinguish those companies. So those companies that will be really successful, I think that they are starting differently. They are making this as transformation project, not automation project.

[00:24:42] - [Speaker 0]
Well, I've loved chatting with you today, and I love your fresh approach and looking at things differently. And I suspect you've set off more than a few light bulb moments today. So for anyone listening that wants to find out more about you, about Blue Chip, about anything we talked about today, Where can they find you?

[00:25:00] - [Speaker 1]
Probably the easiest way is to find me on LinkedIn. I and I post also regularly. You will you will hear very fresh voice because I do not write my post with AI. I come from a Slavic country, I'm very direct. And this is what I what I heard from my post.

[00:25:16] - [Speaker 1]
I I share probably slightly different perspective than than majority of vendors in this area. So I really encourage everyone to to follow me on LinkedIn and follow BlueClip LinkedIn web page where we are also sharing the knowledge, our lessons learned from from different projects, working with clients, and and we hope to, you know, also guide people where to look for too much hype, how to validate what vendors are are telling you, how to find those lies. So this is actually a series that I will be starting. So there will be 10 posts that are being planned to be published from from August, where I will be reviewing some AI lies that you can find on websites of different startups in this area, and why I believe, you know, those are lies, and what didn't work in practice. So I also try to share, you know, so I worked for a 60,000,000,000 US dollar CPG company.

[00:26:16] - [Speaker 1]
It's really important for me that this works. So I really encourage everyone to connect with me on LinkedIn and stay in touch.

[00:26:23] - [Speaker 0]
Yeah. I will echo everything you just said there. And, if anyone in listening is interested in AI, value creation, and the future of business, please check out the links in the show notes. I'll add a link to your LinkedIn, the blue chip website, blue chip LinkedIn page, and all the things that you mentioned there, and people can check that out. And I'd love to stay in touch with you and see how this evolves, maybe get you back on later in the year.

[00:26:47] - [Speaker 0]
But thanks for joining me today. Really appreciate your time.

[00:26:49] - [Speaker 1]
Thank you so much, Neil. I really appreciated this discussion. And I hope that, you know, some people were able to learn something. Maybe we will save them some mistakes. And if anyone has questions or just want to, you know, learn a little bit more, I would be more than happy to support.

[00:27:04] - [Speaker 0]
I think today's conversation was a refreshing antidote to the idea that just spending more money on AI automatically creates more value. As my guest explained, businesses need to fix their data, document what their people know, choose sensible use cases, and stop automating broken processes. But my favorite takeaway was that AI makes knowledge cheaper and content more abundant. Practical experiences, accountability, and genuine human connection could become more valuable than ever. But I'd love to hear your thoughts.

[00:27:38] - [Speaker 0]
Is your company using AI to automate the business it already has or build a better one? As always, techtalksnetwork.com. Let me know. I'd love to hear from you. But that's it.

[00:27:51] - [Speaker 0]
I'm afraid we're out of time now, but I'll be back again tomorrow with another guest. But thank you for listening today, And, hopefully, I will speak with you again tomorrow. Bye for now.