Achieving Tangible Success in the New World of Business

AI is fundamentally reshaping business strategy, making automation, intelligent decision-making, and digital labor essential for staying competitive.

Hear from Ian Gotts, Founder and CEO at Elements.cloud, as he interviews Vala Afshar, Salesforce Chief Digital Evangelist and author of the book “Boundless: A New Mindset for Unlimited Business Success.”

In this future-thinking session, Ian and Vala discussed the transformative power of AI, including the need for businesses to break down data silos and embrace AI holistically, from predictive to autonomous phases. They also touch upon the great need for active experimentation with AI technologies, to challenge dominant logic, and continuously focus on developing skills to stay competitive.

• AI is a Revolution, Not A Trend – Agentic AI is reshaping industries by operating autonomously to improve decision-making, streamline workflows, and scale operations effectively 
• Strong Governance Fuels AI Success – Reliable data, well-structured business processes, and robust governance frameworks are key to ensuring AI delivers meaningful results 
• AI Literacy is Key to Long-Term Success – Staying competitive requires businesses and professionals to build AI expertise, embrace lifelong learning, and strategically integrate AI 

Transcript:

Kalia Garrido: Thank you so much for joining us today. My name is Kalia Garrido, and I head up strategic marketing and events here at HIKE2.

HIKE2 If you don’t know us already, we are a fully functional best in class innovation consultancy, and we specialize in digital transformation, strategy, design and implementations

You are in for a treat today, as we have some seriously smart folks on the line and ready to share their expertise with this group. But before we begin some light housekeeping, this is a webinar, so of course, your cameras and microphones are off, but we do encourage communication and engagement via the Chat, the Q. And a. Or, if you’d like, we can reserve some time at the end of the event for asking questions. We are recording, and this session will be posted out on the HIKE2 Youtube Channel, along with a plethora of other great innovation, forward content that we have there. I’ll be sharing the link here in the chat soon.

And allow me officially to begin by introducing our special guests.

We have Vala Afshar with us. Vala is Salesforce’s chief digital evangelist. He is a world renowned speaker on business digital technologies. He’s a patent holding and holding inventor. He’s a social media contributor with over million followers on Linkedin and Twitter, and he is the host of the popular Weekly Web series devoted to business technology which is called disrupt TV.

He is at heart a super savvy business leader and practitioner, with a successful career as a chief marketing officer, chief customer, officer and Vp. Of engineering at several tech companies before his tenure at Salesforce.

Also, he’s an author, as if we need one more thing, Vala. My goodness, he has recently released his book, boundless, a new mindset for unlimited business success which you can find out on Amazon. So, Vala, thank you so much for joining us today.

Vala Afshar: Thank you so much for the kind intro. Thank you.

Kalia Garrido: Alright and then we have, of course, the one and only Ian Gotts. He is the founder of Elements.cloud their change. Intelligence Platform allows you to speak agent. It is easiest to introduce Ian with numbers, He has written books, and was at Accenture for over years. He’s a customer and a partner of salesforce for over years and he spent years right up there on his soapbox talking about the power of business analysis and building the right thing. Ian. As always, we at HIKE2 are so happy to partner with you, and to have you here with us. Let’s do this. The floor is yours.

Ian Gotts: Well, thank you for those kind introductions, Vala again, thank you for joining me. I love spending time chatting to you. This is the precursor to HIKE2’s Innovation Summit. I don’t think anybody can talk about innovation without thinking about AI and agents, but I mean, there’s lots of hype. So is this a fad? Or do we think actually, this is a major disruptive change.

Vala Afshar: It’s a pleasure to connect with you again. You always expand my mind. So I appreciate you. And and the question, this is the most important technology of my lifetime.

I’ve been in tech for years, and I remember being an undergrad surfing on mosaic and netscape browsers. In the web was launched by Cern to the world. And even though I was studying engineering electrical engineering undergrad at the time. I didn’t really think about this as a killer ingredient of my lifetime. I didn’t realize that it would give birth to Amazon the following year, and Google years and salesforce years after and the most valuable companies on Earth today are internet companies based on market capitalization. And so for a long time I thought the web. If I had to pinpoint the most important technology of my lifetime. Certainly, you know mobile revolution with with this device in the social networking. And you know all of the you and I have experienced so many of the technologies distributed ledgers and and and Internet of things, and the data revolution in the last years but AI and its various form factors.

And now specifically agentic AI, you and I serving in the Salesforce community. We’ve we’ve rode the wave of predictive AI and generative AI. And now we’re in the center of Agentic AI revolution. And so yes, it is not a fad, you know. Please don’t confuse this technology with any other. The impact will be profound. I think it’s electricity for the st century.

It’s of those ingredients that if you ignore you will be in the dark, and it’ll be hard for you to compete and and win and and and thrive in this, in this, in this, in this world, without it.

Ian Gotts: Okay, that’s a pretty bold statement. Oh, and I think also, we need to think about it. We’re looking at it from a business perspective. But I think, obviously from a consumer perspective, it’s going to touch everyone’s lives. And let’s pick that up in a moment. But from a business perspective, I think there’s some expectation. Management needs to happen here. I think people they saw Openai. They gave it lines, and it wrote a poem and went well. In that case it must understand my business. I don’t need to just ask you to do things. It’s kind of not like that from a business perspective. If you want a gentic, AI means you want it to do something.

So it deterministic. You want it to help reschedule a booking. You want it to book, vacate a book, an internal vacation. You want it to summarize a call.

You actually need to give it some instructions. You need to give it some action. So I think it. It requires some foundations. We’ve got to connect it to things. It’s not just going to sit there on its own. So talk to me a bit about what you think. Some of the foundations are from a salesforce perspective.

Vala Afshar: Yeah, I know it’s it’s it’s great that you ground the conversation on what is agent? What is agentic? AI, and advancements in how we understand language.

Over the last, I would say massive advancements over the last to years, and then and then reasoning logic. So an AI agent can understand intent through natural language. One of the st white papers written on natural language processing was what Dr. Richard Socher, you know, former Chief AI officer at Salesforce in he wrote the st set of papers on prompting so understanding, intent through language. planning, and using reasoning and appropriate context.

So you know, understanding and and reasoning through. And you hear, you know, terminology like retrieval, augmented generation, rag, semantic search vector database. All these scientific.

Ian Gotts: Ability.

Vala Afshar: That allow software to be able to reason and then take action. So so understand language, understand reasoning. And at this point you can give it agency to to not be assistive in nature, but autonomous. And and so you know my company for the last year and a half to we’re now building software that does the work. We’re not building software for years. We built software to give to humans. So the humans can do the job.

Now, we’re developing software that does the job alongside us. So taking action using tools to accomplish the task in any sort of jobs can be broken down to composable to set of tasks. And then and then, of course, this is the the superpower of it. It’s improving through interactions and through iteration. So it’s constantly learning. So it’s constantly understanding, conscious, constantly improving its reasoning, constantly improving its fidelity and its ability to precisely take action.

So the reason why this is so important is, you know, if you ask you know, our our founder at Salesforce, our mission, he’s likely to say our goal is to be the number one global provider of digital labor.

And and if you had asked our mission years ago, that would not be the statement. So and I think this is why people are questioning whether it’s fat or real because of the velocity of innovation. The speed and direction is unlike. Again, anything we’ve experienced. You referenced the consumerization of generative AI. In October of and we’re days later million people were using chat Gpt fastest adoption of any tech in our lifetime, ever in any in humanity.

And now, over billion people are using generative AI capabilities. And to answer your question. Yes, in business, where trust is your number one core value. It’s common core value at elements cloud and salesforce. You have to have certain set of capabilities for us. We call it kind of tryout of capabilities. You. It starts with data.

You know, you need to ground your data. You need to have trusted data. That’s both structured data that you have in a Crm and unstructured data you have on your documents and social and all the other majority of the data is unstructured. So there’s the data elements and the importance of having trusted quality data, the application. The applications that we have sales, service, marketing, commerce, tableau slack, you know, we have a variety of customer facing front office applications. And then the agentic layer. And this is where technologies like rag and and language models and all these other derivative sciences within. AI give you the ability to give agency to software.

So you know, you sit back and you realize that? You know, when we talk about hybrid work, it’s no longer a location specific definition. We’re not talking about people and intelligent software, co-creating value and ensuring customer success. And this is a this is a profound, will have profound impact on businesses and individuals and society and culture unlike any other technology.

Ian Gotts: So you talked about a couple of the foundations. One is obviously data, good quality data. And we need decent data governance around that to protect it.

The second, you said, was, we need an application. So to take action. We need something that can post a record or get a record or do some form of action. You need the agentic layer, which is the ability for it to take that natural language, work out what it needs to do build a plan, reason to go and do it. But can I add other things to that list? One is, you need to understand what the business process is.

Vala Afshar: For sure.

Ian Gotts: If you say you want to go this, this should take a call, analyze it, and then schedule a new call. We need to know what that looks like. It can’t magically guess that for your business. So I think well understood business processes. But then the other thing we’re discovering is how fast you need to iterate around these agents you talked about the pace of change. But even if you’ve got an agent relatively quickly, you’ll go. Actually, that I can think of a better way of doing that. So you need a really good implementation life cycle where you’ve got a level of governance.

And because unless you’ve got that governance, no, industry is not just the regulated industries. No one’s going to have the confidence to implement agents unless you know you’ve got a level of governance around it. I think you called it trust, but in terms of trust.

You’ve got to trust your data. You need to trust your process. You need to trust also that you can drive around that cycle relatively quickly. And I think we’re seeing organizations that have got those in place. They have the platform to grow really quickly and actually take advantage of agents. But for many organizations they’re still having to put those building blocks in place.

Vala Afshar: Yeah, no, absolutely. Can you talk to maybe some, maybe some of the customer, either customers or use cases that you’re seeing that that seem to be working well. Sure, let me just what you said is super important and and foundational to all of this, and it was buried in the in the in the trust element.

Yeah, building agents that work reliably, absolutely require strong process fundamentals and all AI projects are data projects. And and so if you’re going to build tools to design and build and scale agentic capabilities in your in your business, small, medium or large, you need to do it with confidence.

We saw this at last week I mean your company. If I’m not mistaken, there were like people standing wall to wall. I don’t think there was any seats available at TDX, our developer conference that we have annually last week, and it was elements that you showed, no matter how outdated or process, no matter how manual the documentation AI can now set up your salesforce orgs for you, and and give you a visual representation of it so instantly visualize how your org actually works. And with no manual effort you can surface, you know, hidden workflows. It’s it’s actual process, not what you thought or what you were told, and that’s how you accelerate agentic applications. And and so you have to have incredible discipline in order to achieve this magical magical experience at my company.

There’s an agentic layer being deployed across all our functions sales, service marketing, every function it we call it business transformation business technology.

My, V2MOM, my, how we performance manage of us at Salesforce. We have this process called V2MOM vision values. The st B’s methods, obstacles, and measurements. Every employee has a V2MOM can be summarized, probably in a page and a half. What’s your vision? What are your values methods, or how you’re going to get to your goals, and then how you’re going to measure success.

We now use agent force to help with our v. amp. So if I say. I want to have keynotes in fiscal Fy.  I use Agentforce, and Agentforce reminds me make sure you get audience survey of % or better with your keynotes. So now my practice is when I speak. At events, I ask for survey feedback because it was Asian force giving me specific metrics. You know, I’m going to write a hundred Zd net articles. It gives me specific elements that identify successful what it means to be a successful columnist. So it’s amazing how my methods and my measurements and my obstacles, because it knows I’m a single contributor. It knows where I sit within salesforce.

So it also gives me potential things that I should be so so as customer just from performance management point of view, I find that I’m aligning my my mission, my goals, my vision more carefully, more methodically, more deliberately, with the company, not my team, my function, my company.

Now as far as customer examples. Again, for years you’ve been serving our community and we’re a sales force. We are a customer of elements. Dot cloud. Thank you for helping us improve our visibility and our and our innovation velocity using your technology.

But whether it’s and you at Tdx and at dreamforce, you hear so many of our customers from, you know, could be a deco. Who’s, you know, Recruitment Company, one of the largest in the world now attempting to one on one be able to serve million folks that use their service to find jobs. And in the past they they didn’t have the ability without agent force to be able to provide custom engagements with this incredible customer base, that they have bike boat bike tours in Europe. Customizing, biking, and sailing trips uniquely to their customers. They’re able to generate tens of thousands of coats now using agents force. These are small companies. They’re not, you know, I can name. Obviously, we have fortune, companies that are using the technology. But this is the beauty of digital labor. Some of the clients and customer success stories you hear may be the st time you heard the company.

But I think it’s important to know that when you can scale your labor, and this is unlike our lifetime, where you know you, you hired salespeople, you can expect units of output. Software developers, units of output. This is not linear when it comes to using intelligent software that’s constantly learning, constantly scaling. And the models are improving at rates that it’s hard to keep up with. To be honest with you.

So it’s a nonlinear impact. It actually reminds me of the innovation we’re seeing with autonomous vehicles. But that’s what we’re experiencing in business so small business today. Now have the opportunity to implement this technology and compete with some of the largest companies on Earth in terms of units of output and ability to deliver with currencies that matter most in today’s economy, speed, intelligence, scale and trust. And that’s the power that I think you can have using using Agent Ki.

Ian Gotts: I think that that scaling is really interesting, because I think that that’s what’s challenging a lot of the a lot of existing industries. If you can. If you’re a small company, you can perform what could be done by a large company, because you’ve got almost infinite capacity. I mean. Thank you. You called out the the product which we launched at Tdx called process configuration mining. We we discovered only it’s it’s taking all of the metadata in an org and then building diagrams so you can see how it works. We talked to a customer, said she just spent $with a consulting firm, having that documented manually, and we’ve just done it in  min. Now you might go. Well, hang on. That’s taking away work from the consulting firm it is. But actually that was, that was not valuable work. If you could have that information, provided the consulting for can then do what they’re really good at, which is then help coach the customer on. There’s a security breach here, potentially or over here. We could do some improvement. So I think we need to look at this as not just it’s it’s replacing jobs. But actually, how do we actually elevate some of those jobs? Now, clearly, jobs are going to move around but part of this is about how AI starts to provide more accurate information. You’ve got a good platform to build on, but I want to take you back to a couple of those examples that you gave. They were very. They were customer facing examples, and I think they are the highest risk examples that you could probably give because there’s liability issues. There’s a unless you’re really confident about what the agents doing. Then I think that there’s a reluctance to to maybe launch some of those quickly, but I think the other one you talked about, which is internally facing employee facing your one for your V mom. The ones we’ve got are internally facing. I think that’s where people need to start lower risk. Your employees will give you feedback. If it doesn’t work the way expected, you can change it. And I think hitting for the sort of the home run like we’re going to put this on our customer facing website. And it’s going to deal with all our prospects. Feels like too big a step at the moment. I know it’s great to have those stories out there. But I think it’s it’s also not necessarily replacing people. It’s actually working alongside. It’s not replacing you. It’s helping you do your V more. So I think we need to bring it back to how do we use agents to make people who are already doing things more effective. And I think that that’s that’s still valid innovation. It’s not about scaling building a business of a hundred million business with people. So I think we need to. I’m sensing at the moment we’re at the very early stages of this, and we and people are struggling about where to start.

Vala Afshar: Yeah, no, it absolutely. You’re absolutely right. I. My assumption is that you know, you’re always customer you’re not gonna launch anything in production and provide service to a paying client unless you’ve test driven the technology whether it’s personalizing experiences. It could be coaching, you know, our our sales professionals at my company have coaching where you have Agentic AI, reviewing your. It’s not just your V2MOM. It could be a video conversation. It could help you draft a more robust email that’s happening also on our services side of the business. It could be create for marketeers. It could be creating campaigns as far as research and development. Just research alone, you and I are prolific writers. You’re much with x books. I suspect. If I look at your phone. You probably have a half a dozen different generative AI tools. I know I have a half a dozen, and I have my favorites. It’s incredible how it’s Turbo charging my research capabilities, providing me links so I can validate to make sure I’m using grounded truth as I’m developing my my thoughts and and sharing the content. So, as you said, you know high value, low risk. But I have to say that you need to not just, you know, dip your toe in the water because, as much as you know, the the accuracy may not quite be there today at the rate of improvement is such that when we have this discussion a year from now. Where today over paying customers are implementing Asian force, thanks to companies like you stock cloud very quickly. This isn’t years of us collectively trying to convince people that cloud is as secure, as safe as your on-premise rack of servers, and believe you me, it took years. You and I know it. My salesforce implementation was and we went live April and believe you me, boardroom discussions in terms of why, our most important asset other than our people, our customer data was moving to this thing called cloud.

I had those debates and discussions for nearly a decade. This isn’t. This is not so, you know it. It, you know. Yes, low risk high value internal. Feel comfortable about it in your sandbox, in your get, you know, get, build, consensus, and trust with your internal stakeholders, but know that you don’t have the luxury of of wait and see, because it’s likely your competitor is going to have an aggressive approach towards assuming they have the processes, assuming they have their governance, assuming that that they have their backyard clean enough to host a barbecue. But this is moving again. A year ago the mission statement of my company would not be today’s mission statement, and and and the amount of investments going into hardware and software because fundamentally, you have to ask yourself, what does it mean to be a healthy company in an AI st economy.

And to be this is like digital Darwinism. You know, Darwin the survival of the fittest. What does it mean to not only survive, but thrive and grow?

And I think you have to have an operating system, an operating model that says you’re able to sense and understand and decide and act. The military actually calls this suda sense, understand, decide, and act where where the Delta T from sensing and acting is converging to 

And and and it’s machine scale. Pseudo is how the military builds like the stealth bomber, or where at some point you actually disengage with the with the pilot because the response time through certain maneuvering is measured in nanoseconds, milliseconds. A human cannot operate a machine at those speeds. What we’re going to find in certain parts of our enterprise is that the speed to value from sensing to acting will require digital labor and you and I, when we are at Tdx, or at any events in San Francisco, chances are we’re in a Waymo.

Chances are we’re gonna be in a fleet of robo taxis in the next few months, and when you’re in a self-driving car, you you it’s a kind of a reminder that we’re building self-driving businesses where there is going to be a machine scale pseuda model in business and it’s machine led human assist for certain functions. Certain repetitive, low value. Frankly, boring tasks where you don’t want someone’s year career doing things that can be done by software. And in time it’s going to be done faster, better. You also realize when you’re an autonomous vehicle, that it’s a different experience and it’s nonlinear impact. When you get to this level autonomy where it’s completely autonomous, where the operator is not is free to, you know, binge, watch Netflix or build element process maps automagically within minutes. You’re no longer operating the vehicle. This is an incredible empowerment to to people in the vehicle. We’re gonna we’re going to experience that. And we’re going to experience that in business, but also the the uneasy part. This is where we have to challenge dominant logic, you and I and folks we serve, and business folks in general.

Once, you see, there’s no steering wheel in the car. Once, you see, there’s no gas or or brake, no pedals, there are no mirrors. There’s no back window. All the human user interfaces are are gone. And you ask yourself, what does the agentic design and business? What would that look like? You know, in the next and years and and so I think the healthiest companies are going to be autonomous companies. And I don’t think you can achieve autonomy without implementation of agentic AI, and and perhaps physical AI, because when we talk about drones and robo taxis and even humanoids at Tdx, you know, saw examples, albeit very early examples of robotics, and how you know this is that car manufacturers are not. This is not new to them, you know. The the st industrial robot was invented in  a year before the st time the word AI was used at Dartmouth College. So around the same time AI and industrial robots, and and and now with autonomous vehicles, with the sensors and cameras and Lidar and software and Gpus and Cpus. This incredibly deeply integrated platform that allows you to you know, have a cognitive download from the human to the to the vehicle. We’re experiencing that in business, and it’s going to be companies like yours and mine that will build the components that will give people the confidence, as you said, to start with these high value, low risk examples but very quickly recognize that you’re going to be delivering these same capabilities, and the complexity of tasks will grow.

And it’s and that’s why it’s important to have process rigor, importance to have governance and data, because you can build a reputation, a lifetime and lose it with one agentic action that’s misaligned to your core values and guiding principles. Guardrails is one of the key components in terms of how we build the agentic framework, as you know. So it’s you know it’s it’s it. The expectation for all of us need to be. You have to. We have to have a beginner’s mindset.

We have to recognize speed is important, and we have to continuously learn, because this is this is this will require us to be at our best.

Ian Gotts: There are so many, so many, so many things I could pull on out from what you were talking about. But let’s pick up a couple of those one is speed is important, so you can’t sit there and go. Well, we’ll do one agent and then give it months and see where we are.

You need to lean in and use this period of time for experimentation, but also a time for building. If you haven’t got great data. If you haven’t got good processes, you’ve got to get on with that like one of the one of the critical resources is measures is time. So I think things are accelerating. So got to lean in. I think the other thing you said was about culture. And I think a culture of I’m sure AI can do that rather than doing it and then going. I wonder if AI could have done it? We are everyone in elements, Cloud. I’m sure the same is true, for your company is now thinking. Well, I’m sure AI could do that, and they think AI first, and if AI can’t do it. Well, then I’ll do it. Or what elements of that activity can AI do for me. So I think there’s a different shift in terms of that. AI first, st which feels like you’re giving up some level of control. But you’re kind of not if you do it properly.

Vala Afshar: Yeah, control is for beginners. You know, when you achieve domain expertise, you realize it’s not about control. It’s about co-creation. It’s about collaboration. The most remarkable people I know are not controlling by. You know you’re the most accessible. You’re always willing to share knowledge, always willing to celebrate best practice, always willing to change your mind when you’re in the presence of something that’s potentially better. So my experience with you is, I’ve never, ever experienced any hint of the desire to be in control in any capacity. You just want to be helpful.

But what you just said in terms of like when you, when you’re starting out on this journey. I think the st thing you have to ask is, what can AI do? This is why staying teachable is important. What can AI do today? And when you go and see new launches of AI every week you have new models that are being launched. And it’s coming from different geographies around the world, which is incredible. It’s questioning the cost models. It’s questioning, how quickly are we going to get to reasoning that’s going to be on par with at a human level. The next question is, what kind of infrastructure is necessary for that? AI. To work for my business.

This is where you need to partner with elements dot cloud or salesforce, because you have to understand. Do I have the data? Do I have the applications? Do I have the agent capabilities.

Is it on a foundation we spent years building hyperforce to ensure? We have a hyperscale and native to our platform and data cloud for us that layer of data, those engineers years working to build that foundational capabilities, bringing Cdp customer data platform, not just in marketing, but across the entire application layer for us. So what kind of infrastructure is necessary? And then what kind of use cases warrant considerations like you said. Do I want to hit the ground running with a customer facing use case without making sure I’ve vetted that capability internally. Is this high risk? Is this going to does this meet my ethical and and privacy and governance requirements? You also have to recognize that when we do a CIO survey today, the number one challenge is data. Silos number is integration data. Silos means that you have trapped data. But it also means you have trapped value.

So once you understand what AI can do. Once you understand your infrastructure readiness for AI’s current capabilities. Once you decide which use cases, I think doing a trap value analysis to recognize. Where are there opportunities for you to delight your internal external stakeholders? Because businesses are full of friction, full of heavy processes, cultural constraints that limit us. Flow is all around us. We just as humans have creative ways of disrupting it. So optimizing flow of value where you can understand trapped value and being able to remediate is important. And then what type of Ro, how do you measure success? How do you measure this digital labor and the level of speed and personalization scale and enhance trust that you’re able to create. So your Roi design and even your relational design, there’s there’s relational intelligence that needs to come into play because we’re the last generation of managers that are gonna manage just people.

Ian Gotts: Okay. So we we’ve just released our new org chart, and the org chart has agents on it.

Vala Afshar: Unbelievable. It doesn’t surprise me, because obviously, you’re a bleeding edge. I mean, you’re in the forefront of doing this. But imagine, years ago as a CEO of the company years ago, years ago. You probably were thinking about this years ago, but the most Ceos didn’t think that calendar they would develop an org chart that would include agentic or digital functions on the org chart. We have our higher ed summit happening this week, Unity Environmental College will be presenting at our summit. Dr. Malak Kalori is going to introduce his org chart at Unity environmental university, student campus. And he has his direct reports that are represented as digital twins via an agentic capability that they’re launching. He has his own. So he’s grounding a language model based on all of the information he uses to make decisions. And he’s making this available to his leadership. So there’s a digital twin of the President of Unity. So think about this isn’t just replication of, you know, and I’ll say, white collar work at the entry level.

These are org chart elements all the way to the highest level represented by intelligent software that has a persona that mirrors a twin of your key key decision makers and key people in your organization. So you have to move fast. You have to decide how fast how important it is for you to move fast? You know, that’s another decision. So what can AI do? Is your infrastructure ready? What type of use? Cases? How do I identify trapped value? How do I measure success? And then ultimately, self reflection in terms of how important is it to go fast? And I would say, have the highest sense of urgency, have a high sense of urgency, because your competitors are not, are are looking to differentiate using this set of capabilities. And as we’re finding out.

It is nonlinear. You know, there’s levels of autonomous vehicles until it’s fully autonomous. You see that nonlinear impact where you’re no longer responsible % for driving a vehicle. You’re now free to do everything else. And there’s positive externalities that’ll come from this autonomous vehicle revolution that we’ll experience years from now, because you will not need as many parking garages as we have today because, as part of managing a fleet of autonomous vehicles. Part of the optimization algorithms would be that these, the fleet is always in motion or mostly in motion. Where today our cars are probably driven %, % parked. So you have dizzy cities that are going to be redesigned. Garage is now a park, a school, a library, a hospital handicap can now operate. Vehicles operate vehicles, so you no longer are excluding certain group of demographics that couldn’t take advantage of of getting from A to B using.

Ian Gotts: Of course.

Vala Afshar: And of course you’re now creating monetization where it’s likely your autonomous vehicle can be summoned into a robo taxi in a gig economy. You know, if you own a Tesla. it’s likely that in the next couple of years you when you go to sleep. True wealth is when you’re making money. When you’re asleep you can. You can. You can send your Tesla into a robo taxi environment and deliver passengers from A to B and and and create a revenue stream for yourself and extend the robo taxi to where private citizens are part of that gig economy. It’s an incredible potential capability. Ark, invest Kathy Wood believes this is a trillion dollar market powered by by AI capabilities. So self-driving cars and will translate to self-driving businesses. And again, it’ll be technologies from companies like yours in mind that will enable this revolution.

Ian Gotts: But let’s just spend a bit more time thinking about an autonomous taxi, because I think that’s a nice analogy for the autonomous business, because you’ve looked at tonight there’s clearly value for for the passenger. But then it’s all the other things you talked about, Parks. You don’t need as much parking, therefore they could be turned into something else. There’ll be fewer accidents, so that will also affect you. Think about the entire supply chain. How many we know we saw during Covid. People weren’t driving as much. There were far fewer accidents.

Vala Afshar: Yeah.

Ian Gotts: Autonomous vehicles have far fewer accidents, because they don’t bump into each other. The.

Vala Afshar: miles is so way more cars are are reporting miles of driving in between police reported accidents. So far safer police reported accidents in way, more cars than than cars operated by humans, and the cost per mile will be an order of magnitude less with autonomous vehicles, so it’s less cost to operate and far safer. And according to again, I’ll reference arc. But there are other studies, even though the robotaxi market is by could be potentially trillion with million autonomous vehicles on the road. The enterprise value, the companies that are building the software, the hardware and the platform is trillion.

The entire GDP of EU is trillion. Just to give you a sense of what these numbers. These numbers are, you know, and of course these are bullish numbers. They’re conservatives, numbers as well and average. But so I’m giving. I’m sharing the bullish numbers, the positive externalities from safer, more cost, effective, and also the stakeholders that will benefit, and the city designs that will manifest itself from this positive externalities will be incredibly incredibly important, and it also will shed light on waste removal, not cost removal, optimizing for autonomous, self-driving vehicle or business. Well, the unintended consequences that because we’re building with incredible precision and the composability and the process rigor that you mentioned and the data governance we’re now operating like surgeons. Because you know where it’s becoming an algorithm. So we have to be very precise, very deliberate. What this means that we’re able to identify waste more deliberately, and all waste are costly, but not all costs are wasteful.

So often today in business, we’re driven to reduce cost and we end up achieving value atrophy because we look at the absolute cost of something, and if it’s high we’ll remove it. Not recognizing the value that’s associated with that cost. So I think the lens need to focus, and we’ll focus more on waste reduction versus cost reduction because we can all agree. All waste is costly, and this agentic layer will very quickly help us identify, because companies like yours in minutes can provide a process map. And now we look at that process, mango, why are we looping here so many times before we exit. What is this other set of stakeholders that are being invited into this process without them adding value? Why are we stuck? Why is there unnecessary friction? The reason why you had the number one session at our developer conference last week is because we’re all visual learners. % of what we process is visual in nature, and when you can have one end of the spectrum where someone’s spending half a million dollars and weeks months later, you’re getting a drawing of their process. And, by the way, as the process changes, you can forget that half a million you just spend, it’s out of date. You within minutes are giving us a visual representation of actual and continuously updating that in real time. How can someone compete with you?

I mean, that’s the capability, because your sense understanding, deciding and acting your suda as a delta T convergence to not quite but minutes. Eventually we’ll probably be a few seconds. But machine scale Suda is how you compete and win, and without agentic layer as part of your business without digital labor.

I just don’t see how you can do it. So it goes back to my st answer to your st question. No, it’s not a fad, and yes, I think it’s electricity for the st century.

Ian Gotts: I think one of the things I heard, which is the only place you find agentic ahead of simplifiers in the dictionary. I mean, you’ve got to simplify st before you start applying it. I think we we, for people who don’t like change, we probably scared them witless. So can we just take this home and just think about what are some of the how would you future proof, your career? Where would you? What are the skills? I think that you need to learn to be relevant in this new world.

Vala Afshar: What a great, what a great question! What a great question!

Years ago, when my daughter was a freshman in High school. I strongly encourage her to to learn software development.

So by her junior year in high school she was teaching coding, and so Junior Year High School senior year, high school coding, and in all years of college she was coding. She. She went to school, studied computer science at Bentley, a Business school, Bentley University, a local Boston University actually in Waltham suburbs of Boston. So anyway, she has a full-time job. She was offered a full-time job as a junior figure salary at years old. She graduates in May. She’s going to start her dad. It took me, I don’t know. years to get to figures. My year old, daughter, but she she’s a proficient in Python Matlab, Julia Scala, Java Javascript. She’s been doing great programming specific to Chatbots, and and she did the so. So that’s my year old daughter.

My year old son is a freshman in high school. I don’t have the same vigor enthusiasm about software as a career. Because I see millions of lines of code at my company now written by AI.

 I don’t know. Half of Github, I think, is AI produced new code, and more and more. The frontier

 developers are speaking to the pace of capabilities. So anyway. Personal story. I’m a little less confident as I was, although I still think writing code is important. The hottest programming language now is English. So you know you should be, you know. And I think prompt engineering is programming. And I think program system thinking chaos theory network theory. There’s a lot of things that software developers and programmers have in terms of how they think about it. So I do think that’s still viable, as someone you know, who is involved in hiring incredible folks into my company. I can tell you high rate of learning and good judgment.

High rate of learning and good judgment will always be I can’t imagine that you’re going to have an interview whether you’re a Liberal Arts Major, or you’re an electrical engineer like myself or my daughter, who’s computer science, or my middle daughter who’s a freshman in college studying economics and data. She’s data, analytics and economics. I can’t imagine you have an interview where the employer is not going to ask. What’s your favorite Gen. AI tool? Tell me how you solve the problem using AI, and it may be your your liberal arts writing, and for me Claude is the best ghostwriter that I use. I find Claude understands me more than any other language model.

You know, Grammarly helps me organize my writing better. Grammarly keyboard. I have a bunch. But but anyway, to answer your question, rate of learning. So use use these technologies. You want to future proof. Your career. Know that next time you’re in interview. If I’m interviewing someone I’m going to say, show me your phone, and I better see a half a dozen AI tools that you’re using you know whether it’s Chat Gpd or or Gemini, or grok or grammarly, or perplexity, or agent force, or whatever it may be. So get in the game trailhead trailhead. You know we have million active learners on trailhead understanding, generative AI modules. We have prompt engineering, we have data literacy. We have, knowing how to solve problems, ethical judgment.

There are all these tracks we have that touches the core components of what we mean by predictive, generative agentic. AI, but also periphery set of capabilities and skills you need. So and these are available to, you know, at at no cost. So stay teachable. Take courses that challenge your rate of learning earn a mentor and a sponsor. When someone shows you that they’re proficient. I know you have employees that have been with the company only months, and they’re producing unbelievable results using your AI tools. And these are folks that didn’t come in as AI experts. But because elements AI has an environment, a culture where experimentation is celebrated because people aren’t afraid of failure, they’re afraid of blame. So when you have a CEO that encourages like you encourages your staff to use the tools when you actually put AI on an org chart. And you say, listen, this is important. This is the identity of our company you give them. You give them the permission to to try to explore, to truly be trailblazers. So, finding a mentor and a sponsor that gives you safe space to do that, I think, is the best thing you can do for your career. I don’t know. Future proofing career, I think, is probably the hardest question to ask right now because because it’s this, this technology will have profound impact on how we shift resources, how we hire, how we retain and ultimately how we do the work that needs to be done.

Ian Gotts: I would say this because I’ve been in my soapbox for the last years, but it feels like business. Analysts are starting to be recognized. You talked about reducing waste. You talked about understanding what the process was. The business analyst skills, the architecture skills, those higher levels, the skills that are earlier in the food chain in terms of before you start building, feel like they’re going to be important. And I think that sounds like quite a generic answer. Yeah, it is. But then think about what your industry or discipline specialization is. You can’t be. You can’t just say I do. And I do sales. What does that mean? Yeah, I really understand. I was having a call just earlier with super switch on, woman, she said. I’m in the finance industry, I understand regulated industries. I’m thinking about agents from that perspective perfect. So you’ve now narrowed it down. It’s not just agents in general. It’s an industry that you know about leaning on that expertise.

So I think I remember when I joined Accenture, you you joined Accenture as a as a graduate, but then, within years you were in an industry stream, and once you were in that industry stream, you pretty much would. I mean because you would deeply understood that industry you weren’t going to change. I ended up in aerospace and defense, which meant I was never gonna be in Central London. Everyone in banking and insurance was in Central London all the time.

Vala Afshar: The Offer.

Ian Gotts: Years of experience. You pretty much couldn’t change industry, and it’s very difficult to do that, and that that’s still really valuable. The in-depth knowledge about how an industry works, and then how a discipline works like, how sales works, or how operations, or Rev. Ops those sorts of things. So I think, leaning into those. And for many people on the call, you probably already have some of those skills. You just haven’t seen this valuable. Oh, yeah, yes, of course I know the logistics industry, but I need to know about tech no understanding the logistics. Industry is becoming will become even more valuable, because that’s how you will generate and identify. Use cases. That’s how you will understand how to simplify. It’ll be how you understand how that industry will change dramatically.

Sure. Well, I think we do really interesting time now.

Vala Afshar: Yeah, absolutely. I would just say that I’m reflecting on my own career, my own you know, and I give credit to my graduate school advisor who helped me improve my thinking, but you know I operated by learning by analogy. I would say I was. I was trying to be a good cook. Somebody would give me a recipe, and I would do a good job following the recipe. Now, if the recipe was lost, I probably couldn’t make a delicious meal because I was learning by analogy, memorization, and and and and mimicking, replicating, but not learning, based on st principles. not learning like a chef, a chef understands the taste of each ingredient. So when a recipe is missing, a good chef can just mix different ingredients and create something delicious.

Ian Gotts: Yeah.

Vala Afshar: But chef is constantly challenging and exploring and tasting and cooking and testing constantly. So there’s a level of curiosity that separates a chef from a cook and you are an explorer. You are a beginner’s mindset. So my advice is, please learn, based on st principles, and if it means fine tuning your domain, expertise within an industry.

Ian Gotts: Yeah.

Vala Afshar: So you can in an absence. And I say this also because I think we need to throw away some old playbooks. We need to throw away some recipes. What you use to build a powerful, scalable, trustworthy business today, if it’s not operating at machine scale, Suda may not be able to have the same level. In fact, not. May will not have the same level of success. So we need more chefs in business unless cooks.

And there’s an apprenticeship, you know. Cooks become chef when they learn from another chef. So this doesn’t mean you’re on your own. You will continue to learn by analogy, but you have to dig deep, and you have to really understand st principles approach to to improving yourself. So let’s be more like chefs and less like cooks, and I think you’ll have a good career. Hopefully.

Ian Gotts: And that’s feels like a perfect way to end this. Thank you, Vala, for spending time today.

Vala Afshar: Thank you. Thank you. Ian.

Kalia Garrido: This is a fantastic conversation, guys. I’m sitting here just riveted the whole time. I love it, Ian, you said. Maybe this feels scary for people who are, you know, kind of a little hesitant to lean into such a great scale of change. I think it sounds invigorating. I think you both have done a fantastic job of showing some of the positive sides of how this is going to benefit us as a society, and where we get to experience new things, and where we can offload some of those high volume, low output tasks that we do to agents, and, you know, kind of free us up to to learn to be better chefs. I think this is awesome. Thank you both so much for sharing your expertise with the HIKE2 audience. My final plug here is that we have the Innovation Summit coming. If you’ve liked what you’ve heard today when it comes to forward thinking topics, please join us in Pittsburgh. It’s on. It’s in weeks depending. When you’re listening to this, it’s March th and th Ian will be there to share his expertise with us on site. So again, Vala Ian, thank you both so much for this conversation. I, personally have learned a lot, and it’s it’s exciting for really what the future holds for all of us.