How AI is Changing Tech Consulting
Reflections on how consulting companies needs to evolve themselves for a new kind of consulting services
Current State
If you are someone who work in the professional services domain for enterprise software. You have had your fair share of endless commentary on extinction of SaaS in an AI Agent world. While the timelines for such an extinction event is up for a debate - one things we all must agree at this point that the change is inevitable. It's coming. When? We don’t know but my experience working within this domain for more than decade tells me that its coming faster than we thought.
Well, I don’t want to dwell any further on this debate. My whole intention of writing this is to how you as an enterprise software system integrator can prepare yourselves for what's coming. As mentioned earlier, I am someone who have spent over a decade in this space. I have seen OnPrem ERP/CRM evolve into B2B SaaS. From Machine Learning use cases embedded into workflows to now fully autonomous agents. I have witnessed it all. I got my first lessons into ERP as a Business Analyst for CGI's made for government Advantage ERP. Spent time with a Microsoft & Oracle SI in the USA. Went on to work for Oracle as part of their Fusion GTM team and now associated with Microsoft as part of the AI Business Process team. The point I am trying to make here is - I am someone who definitely knows a thing or two about this space.
(Note: I am writing this in my personal capacity. Views expressed are my own and not of my employer.)
Now that we have taken intros out of the way, let's get straight to it. Here is a summary of what's coming ahead of us. The new (software) world order!
This new world order will be established by Agents.
Every business process will have an Agent. Finance, Supply Chain, HR, Sales, Service, Marketing, and many more…
Don’t confuse this for AI Assistant (ChatGPT, Gemini, Claude, Copilot, and others are AI Assistants). Think of them as your silent partner for all the work you do, quietly augmenting you.
Agents are like team members who are capable of automating business processes. (think of them as the task doers)
In this new world we will end up having lots of agents. If we were to believe IDC they say there will be 1.3 billion agents by 2028. Agents will be like the internet as we know it today. There are millions of sites on the internet, and the clever folks at Google and Yahoo gave us a way to get to the website we need. Similarly there will be new interfaces that will help us discover these Agents. Essentially the AI-Assistant will become your go to place to look for Agents.
Professional services too need to evolve its business and operating model for the agent-native world. Leaders who win will not be the fastest to adopt AI but those who define and defend the human value they sell.
Allow me to break this down for you. First, you need to see this as an opportunity to reinvent your organization and not see AI as a threat.
Look, we all have done shifts and pivots in our lives. It's never easy and we must start with some hard questions. Ask, what customer value do I deliver that cannot be replaced by AI.
You need to double down on your subtle judgment that you have cultivated over years, Leverage contextual expertise you and your team have harnessed by working 1000's man hours on complex projects, and
Finally, trust-based relationships that you have sustained over the years to give you that first pass at trying something new.
Okay, I hope you all fired up and ready to execute now. Because, now is the time we will turn the heat up on How to make this happen.
I am sure you have heard about the company called Palantir (If haven't - Go Google it or I must say ChatGPT it). Yes, the same company whose stocks are hot right now, and everybody wants a piece of it. Few years ago, it was dismissed by many as a glorified staff augmentation company. Now has a market cap of over 400 bn dollars. There are lessons for professional services leaders from Palantir's playbook. Let's dive in.
Tackling Real and Difficult Challenges:
When Palantir launched itself they didn't go after the easy - they went for the tough problems across complex industries such as Aerospace, Manufacturing, Healthcare and Cybersecurity.
Reimagining your business as a system integrator or implementation partner means you need to look for complex use cases that are unlikely to be provided off the shelf by software vendors as agents or are unlikely to be built by companies on their own. Enterprise software partners have been really good at building accelerators or, industry add-ons on top of ERPs, CRMs and other business applications. However, building for the AI-first world will be different. It will require a very different approach as the way products are built has fundamentally changed.
How? Let's explore this with an example. OpenAI's latest launch of Codex - a coding agents that can write, edit, and understand code. From start (the first lines of code written) to finish, the whole product was built in just 7 weeks. The team consisted ~8 engineers, ~4 researchers, 2 designers, 2 GTM and a PM. We are talking about a consumer facing app which as of 6th October 2025 had its daily usage of has grown by more than 10x since early August, and GPT‑5-Codex is one of OpenAI's fastest growing models ever, serving over 40 trillion tokens in the three weeks since launch.
Three key areas where the professional services leaders needs to focus.
Culture:
First area to tackle in your organization is the Culture. You need a bottoms up, meritocratic culture where there is strong bias for actions. There must've been ~3-4 different Codex prototypes floating around within OpenAI before they decided to push for a launch. These efforts were usually taken by a small handful of individuals without asking permission. Another lesson from OpenAI's culture playbook would be the agility and fluidity - they pivot[s] instantly. It's much better to do the right thing as you get new information, vs decide to stay the course just because you had a plan.
I have often seen firms pretending to be Know-it-all. The reality, customers can see through this. You and your client facing teams must come across as a trusted advisors.
You must attract and retain unusually high-talent-density teams, with strong emphasis on curiosity and intensity, not just technical skill or prestige. To do this, use unconventional interview formats, testing for cultural and intellectual fit alongside skills.
Internal disagreement, transparency, and psychological safety can power rapid learning and prevent groupthink. Build mechanisms for junior voices to challenge orthodoxy and experiment. Initiate and champion open debates on technical and ethical directions within internal communications.
Context:
To understand this part, we will go back to Palantir's playbook. Palantir generally divided its engineers into two types:
Forward deployed engineers - FDE (Engineers who work with customers onsite)
Product development - PD (Engineers who work on the core product team)
An ex-Palantir employee provides us more insights into this model.
"There’s a lot to unpack about this model, but the key idea is that you gain intricate knowledge of business processes in difficult industries (manufacturing, healthcare, intel, aerospace, etc.) and then use that knowledge to design software that actually solves the problem. The PD engineers then ‘productize’ what the FDEs build, and – more generally – build software that provides leverage for the FDEs to do their work better and faster.
This is how much of the Foundry product took initial shape: FDEs went to customer sites, had to do a bunch of cruft work manually, and PD engineers built tools that automated the cruft work. Need to bring in data from SAP or AWS? Here’s Magritte (a data ingestion tool). Need to visualize data? Here’s Contour (a point and click visualization tool). Need to spin up a quick web app? Here’s Workshop (a Retool-like UI for making webapps). Eventually, you had a damn good set of tools clustered around the loose theme of ‘integrate data and make it useful somehow’."
This model essentially allowed Palantir to pull off a rare pivot from service company --> product company. (Palantir has 80% gross margin in 2023 vs Accenture's 32%)
Direct immersion in client environment via approaches like the FDE mode permits accelerated domain learning, builds trust, and results in highly relevant solutions. Professional services leaders should consider secondments, embedded consulting, or client co-location as mechanisms to deepen impact and understanding. Real enterprise value especially in complex sectors, emerges from mutual trust and firsthand context, not distant analysis.
Agents are only as good as the context they are provided, context is that which is scarce would be the foundational insights your agents will need off course with companies data it can reason and perform actions. But for you to be able to build a right product, for a right use case, that solve a real problem can only come from the context that you and your team have for the industry, process, and people who work on them.
Having said that, if you are in the business for a long time and have built solutions for industries - chances are that you have this context already available. Even if you haven't built solutions but simply implemented OEM software's, this context will be tribal knowledge that is sitting across your people - your functional consultants, your technical consultants, your solution architects, you onsite PM - they all have learnt a great deal of customers business and pain areas. Its time you harvest that knowledge and leverage it to build for the AI-first world.
Tools I Tried (and Dropped)
There are plenty of shiny tools that promise more focus, more output, or better organization. I’ve tried them—Scrivener, Ulysses, Roam, a half-dozen markdown editors. They all seemed great for a week, but I always ended up back in Google Docs and Notion. Simpler works better for me. I don’t need features I’ll never use.
How to Pick Tools That Work for You
Don’t chase what’s trending. Pick tools that make you want to write. If you find yourself fiddling with settings more than drafting words, drop it. Stick with what you’ll actually open every day. Don’t be afraid to quit a tool when it stops helping. Writing is about getting words down. The right tool is the one you’ll use.
Current State
If you are someone who work in the professional services domain for enterprise software. You have had your fair share of endless commentary on extinction of SaaS in an AI Agent world. While the timelines for such an extinction event is up for a debate - one things we all must agree at this point that the change is inevitable. It's coming. When? We don’t know but my experience working within this domain for more than decade tells me that its coming faster than we thought.
Well, I don’t want to dwell any further on this debate. My whole intention of writing this is to how you as an enterprise software system integrator can prepare yourselves for what's coming. As mentioned earlier, I am someone who have spent over a decade in this space. I have seen OnPrem ERP/CRM evolve into B2B SaaS. From Machine Learning use cases embedded into workflows to now fully autonomous agents. I have witnessed it all. I got my first lessons into ERP as a Business Analyst for CGI's made for government Advantage ERP. Spent time with a Microsoft & Oracle SI in the USA. Went on to work for Oracle as part of their Fusion GTM team and now associated with Microsoft as part of the AI Business Process team. The point I am trying to make here is - I am someone who definitely knows a thing or two about this space.
(Note: I am writing this in my personal capacity. Views expressed are my own and not of my employer.)
Now that we have taken intros out of the way, let's get straight to it. Here is a summary of what's coming ahead of us. The new (software) world order!
This new world order will be established by Agents.
Every business process will have an Agent. Finance, Supply Chain, HR, Sales, Service, Marketing, and many more…
Don’t confuse this for AI Assistant (ChatGPT, Gemini, Claude, Copilot, and others are AI Assistants). Think of them as your silent partner for all the work you do, quietly augmenting you.
Agents are like team members who are capable of automating business processes. (think of them as the task doers)
In this new world we will end up having lots of agents. If we were to believe IDC they say there will be 1.3 billion agents by 2028. Agents will be like the internet as we know it today. There are millions of sites on the internet, and the clever folks at Google and Yahoo gave us a way to get to the website we need. Similarly there will be new interfaces that will help us discover these Agents. Essentially the AI-Assistant will become your go to place to look for Agents.
Professional services too need to evolve its business and operating model for the agent-native world. Leaders who win will not be the fastest to adopt AI but those who define and defend the human value they sell.
Allow me to break this down for you. First, you need to see this as an opportunity to reinvent your organization and not see AI as a threat.
Look, we all have done shifts and pivots in our lives. It's never easy and we must start with some hard questions. Ask, what customer value do I deliver that cannot be replaced by AI.
You need to double down on your subtle judgment that you have cultivated over years, Leverage contextual expertise you and your team have harnessed by working 1000's man hours on complex projects, and
Finally, trust-based relationships that you have sustained over the years to give you that first pass at trying something new.
Okay, I hope you all fired up and ready to execute now. Because, now is the time we will turn the heat up on How to make this happen.
I am sure you have heard about the company called Palantir (If haven't - Go Google it or I must say ChatGPT it). Yes, the same company whose stocks are hot right now, and everybody wants a piece of it. Few years ago, it was dismissed by many as a glorified staff augmentation company. Now has a market cap of over 400 bn dollars. There are lessons for professional services leaders from Palantir's playbook. Let's dive in.
Tackling Real and Difficult Challenges:
When Palantir launched itself they didn't go after the easy - they went for the tough problems across complex industries such as Aerospace, Manufacturing, Healthcare and Cybersecurity.
Reimagining your business as a system integrator or implementation partner means you need to look for complex use cases that are unlikely to be provided off the shelf by software vendors as agents or are unlikely to be built by companies on their own. Enterprise software partners have been really good at building accelerators or, industry add-ons on top of ERPs, CRMs and other business applications. However, building for the AI-first world will be different. It will require a very different approach as the way products are built has fundamentally changed.
How? Let's explore this with an example. OpenAI's latest launch of Codex - a coding agents that can write, edit, and understand code. From start (the first lines of code written) to finish, the whole product was built in just 7 weeks. The team consisted ~8 engineers, ~4 researchers, 2 designers, 2 GTM and a PM. We are talking about a consumer facing app which as of 6th October 2025 had its daily usage of has grown by more than 10x since early August, and GPT‑5-Codex is one of OpenAI's fastest growing models ever, serving over 40 trillion tokens in the three weeks since launch.
Three key areas where the professional services leaders needs to focus.
Culture:
First area to tackle in your organization is the Culture. You need a bottoms up, meritocratic culture where there is strong bias for actions. There must've been ~3-4 different Codex prototypes floating around within OpenAI before they decided to push for a launch. These efforts were usually taken by a small handful of individuals without asking permission. Another lesson from OpenAI's culture playbook would be the agility and fluidity - they pivot[s] instantly. It's much better to do the right thing as you get new information, vs decide to stay the course just because you had a plan.
I have often seen firms pretending to be Know-it-all. The reality, customers can see through this. You and your client facing teams must come across as a trusted advisors.
You must attract and retain unusually high-talent-density teams, with strong emphasis on curiosity and intensity, not just technical skill or prestige. To do this, use unconventional interview formats, testing for cultural and intellectual fit alongside skills.
Internal disagreement, transparency, and psychological safety can power rapid learning and prevent groupthink. Build mechanisms for junior voices to challenge orthodoxy and experiment. Initiate and champion open debates on technical and ethical directions within internal communications.
Context:
To understand this part, we will go back to Palantir's playbook. Palantir generally divided its engineers into two types:
Forward deployed engineers - FDE (Engineers who work with customers onsite)
Product development - PD (Engineers who work on the core product team)
An ex-Palantir employee provides us more insights into this model.
"There’s a lot to unpack about this model, but the key idea is that you gain intricate knowledge of business processes in difficult industries (manufacturing, healthcare, intel, aerospace, etc.) and then use that knowledge to design software that actually solves the problem. The PD engineers then ‘productize’ what the FDEs build, and – more generally – build software that provides leverage for the FDEs to do their work better and faster.
This is how much of the Foundry product took initial shape: FDEs went to customer sites, had to do a bunch of cruft work manually, and PD engineers built tools that automated the cruft work. Need to bring in data from SAP or AWS? Here’s Magritte (a data ingestion tool). Need to visualize data? Here’s Contour (a point and click visualization tool). Need to spin up a quick web app? Here’s Workshop (a Retool-like UI for making webapps). Eventually, you had a damn good set of tools clustered around the loose theme of ‘integrate data and make it useful somehow’."
This model essentially allowed Palantir to pull off a rare pivot from service company --> product company. (Palantir has 80% gross margin in 2023 vs Accenture's 32%)
Direct immersion in client environment via approaches like the FDE mode permits accelerated domain learning, builds trust, and results in highly relevant solutions. Professional services leaders should consider secondments, embedded consulting, or client co-location as mechanisms to deepen impact and understanding. Real enterprise value especially in complex sectors, emerges from mutual trust and firsthand context, not distant analysis.
Agents are only as good as the context they are provided, context is that which is scarce would be the foundational insights your agents will need off course with companies data it can reason and perform actions. But for you to be able to build a right product, for a right use case, that solve a real problem can only come from the context that you and your team have for the industry, process, and people who work on them.
Having said that, if you are in the business for a long time and have built solutions for industries - chances are that you have this context already available. Even if you haven't built solutions but simply implemented OEM software's, this context will be tribal knowledge that is sitting across your people - your functional consultants, your technical consultants, your solution architects, you onsite PM - they all have learnt a great deal of customers business and pain areas. Its time you harvest that knowledge and leverage it to build for the AI-first world.
Tools I Tried (and Dropped)
There are plenty of shiny tools that promise more focus, more output, or better organization. I’ve tried them—Scrivener, Ulysses, Roam, a half-dozen markdown editors. They all seemed great for a week, but I always ended up back in Google Docs and Notion. Simpler works better for me. I don’t need features I’ll never use.
How to Pick Tools That Work for You
Don’t chase what’s trending. Pick tools that make you want to write. If you find yourself fiddling with settings more than drafting words, drop it. Stick with what you’ll actually open every day. Don’t be afraid to quit a tool when it stops helping. Writing is about getting words down. The right tool is the one you’ll use.
Current State
If you are someone who work in the professional services domain for enterprise software. You have had your fair share of endless commentary on extinction of SaaS in an AI Agent world. While the timelines for such an extinction event is up for a debate - one things we all must agree at this point that the change is inevitable. It's coming. When? We don’t know but my experience working within this domain for more than decade tells me that its coming faster than we thought.
Well, I don’t want to dwell any further on this debate. My whole intention of writing this is to how you as an enterprise software system integrator can prepare yourselves for what's coming. As mentioned earlier, I am someone who have spent over a decade in this space. I have seen OnPrem ERP/CRM evolve into B2B SaaS. From Machine Learning use cases embedded into workflows to now fully autonomous agents. I have witnessed it all. I got my first lessons into ERP as a Business Analyst for CGI's made for government Advantage ERP. Spent time with a Microsoft & Oracle SI in the USA. Went on to work for Oracle as part of their Fusion GTM team and now associated with Microsoft as part of the AI Business Process team. The point I am trying to make here is - I am someone who definitely knows a thing or two about this space.
(Note: I am writing this in my personal capacity. Views expressed are my own and not of my employer.)
Now that we have taken intros out of the way, let's get straight to it. Here is a summary of what's coming ahead of us. The new (software) world order!
This new world order will be established by Agents.
Every business process will have an Agent. Finance, Supply Chain, HR, Sales, Service, Marketing, and many more…
Don’t confuse this for AI Assistant (ChatGPT, Gemini, Claude, Copilot, and others are AI Assistants). Think of them as your silent partner for all the work you do, quietly augmenting you.
Agents are like team members who are capable of automating business processes. (think of them as the task doers)
In this new world we will end up having lots of agents. If we were to believe IDC they say there will be 1.3 billion agents by 2028. Agents will be like the internet as we know it today. There are millions of sites on the internet, and the clever folks at Google and Yahoo gave us a way to get to the website we need. Similarly there will be new interfaces that will help us discover these Agents. Essentially the AI-Assistant will become your go to place to look for Agents.
Professional services too need to evolve its business and operating model for the agent-native world. Leaders who win will not be the fastest to adopt AI but those who define and defend the human value they sell.
Allow me to break this down for you. First, you need to see this as an opportunity to reinvent your organization and not see AI as a threat.
Look, we all have done shifts and pivots in our lives. It's never easy and we must start with some hard questions. Ask, what customer value do I deliver that cannot be replaced by AI.
You need to double down on your subtle judgment that you have cultivated over years, Leverage contextual expertise you and your team have harnessed by working 1000's man hours on complex projects, and
Finally, trust-based relationships that you have sustained over the years to give you that first pass at trying something new.
Okay, I hope you all fired up and ready to execute now. Because, now is the time we will turn the heat up on How to make this happen.
I am sure you have heard about the company called Palantir (If haven't - Go Google it or I must say ChatGPT it). Yes, the same company whose stocks are hot right now, and everybody wants a piece of it. Few years ago, it was dismissed by many as a glorified staff augmentation company. Now has a market cap of over 400 bn dollars. There are lessons for professional services leaders from Palantir's playbook. Let's dive in.
Tackling Real and Difficult Challenges:
When Palantir launched itself they didn't go after the easy - they went for the tough problems across complex industries such as Aerospace, Manufacturing, Healthcare and Cybersecurity.
Reimagining your business as a system integrator or implementation partner means you need to look for complex use cases that are unlikely to be provided off the shelf by software vendors as agents or are unlikely to be built by companies on their own. Enterprise software partners have been really good at building accelerators or, industry add-ons on top of ERPs, CRMs and other business applications. However, building for the AI-first world will be different. It will require a very different approach as the way products are built has fundamentally changed.
How? Let's explore this with an example. OpenAI's latest launch of Codex - a coding agents that can write, edit, and understand code. From start (the first lines of code written) to finish, the whole product was built in just 7 weeks. The team consisted ~8 engineers, ~4 researchers, 2 designers, 2 GTM and a PM. We are talking about a consumer facing app which as of 6th October 2025 had its daily usage of has grown by more than 10x since early August, and GPT‑5-Codex is one of OpenAI's fastest growing models ever, serving over 40 trillion tokens in the three weeks since launch.
Three key areas where the professional services leaders needs to focus.
Culture:
First area to tackle in your organization is the Culture. You need a bottoms up, meritocratic culture where there is strong bias for actions. There must've been ~3-4 different Codex prototypes floating around within OpenAI before they decided to push for a launch. These efforts were usually taken by a small handful of individuals without asking permission. Another lesson from OpenAI's culture playbook would be the agility and fluidity - they pivot[s] instantly. It's much better to do the right thing as you get new information, vs decide to stay the course just because you had a plan.
I have often seen firms pretending to be Know-it-all. The reality, customers can see through this. You and your client facing teams must come across as a trusted advisors.
You must attract and retain unusually high-talent-density teams, with strong emphasis on curiosity and intensity, not just technical skill or prestige. To do this, use unconventional interview formats, testing for cultural and intellectual fit alongside skills.
Internal disagreement, transparency, and psychological safety can power rapid learning and prevent groupthink. Build mechanisms for junior voices to challenge orthodoxy and experiment. Initiate and champion open debates on technical and ethical directions within internal communications.
Context:
To understand this part, we will go back to Palantir's playbook. Palantir generally divided its engineers into two types:
Forward deployed engineers - FDE (Engineers who work with customers onsite)
Product development - PD (Engineers who work on the core product team)
An ex-Palantir employee provides us more insights into this model.
"There’s a lot to unpack about this model, but the key idea is that you gain intricate knowledge of business processes in difficult industries (manufacturing, healthcare, intel, aerospace, etc.) and then use that knowledge to design software that actually solves the problem. The PD engineers then ‘productize’ what the FDEs build, and – more generally – build software that provides leverage for the FDEs to do their work better and faster.
This is how much of the Foundry product took initial shape: FDEs went to customer sites, had to do a bunch of cruft work manually, and PD engineers built tools that automated the cruft work. Need to bring in data from SAP or AWS? Here’s Magritte (a data ingestion tool). Need to visualize data? Here’s Contour (a point and click visualization tool). Need to spin up a quick web app? Here’s Workshop (a Retool-like UI for making webapps). Eventually, you had a damn good set of tools clustered around the loose theme of ‘integrate data and make it useful somehow’."
This model essentially allowed Palantir to pull off a rare pivot from service company --> product company. (Palantir has 80% gross margin in 2023 vs Accenture's 32%)
Direct immersion in client environment via approaches like the FDE mode permits accelerated domain learning, builds trust, and results in highly relevant solutions. Professional services leaders should consider secondments, embedded consulting, or client co-location as mechanisms to deepen impact and understanding. Real enterprise value especially in complex sectors, emerges from mutual trust and firsthand context, not distant analysis.
Agents are only as good as the context they are provided, context is that which is scarce would be the foundational insights your agents will need off course with companies data it can reason and perform actions. But for you to be able to build a right product, for a right use case, that solve a real problem can only come from the context that you and your team have for the industry, process, and people who work on them.
Having said that, if you are in the business for a long time and have built solutions for industries - chances are that you have this context already available. Even if you haven't built solutions but simply implemented OEM software's, this context will be tribal knowledge that is sitting across your people - your functional consultants, your technical consultants, your solution architects, you onsite PM - they all have learnt a great deal of customers business and pain areas. Its time you harvest that knowledge and leverage it to build for the AI-first world.
Tools I Tried (and Dropped)
There are plenty of shiny tools that promise more focus, more output, or better organization. I’ve tried them—Scrivener, Ulysses, Roam, a half-dozen markdown editors. They all seemed great for a week, but I always ended up back in Google Docs and Notion. Simpler works better for me. I don’t need features I’ll never use.
How to Pick Tools That Work for You
Don’t chase what’s trending. Pick tools that make you want to write. If you find yourself fiddling with settings more than drafting words, drop it. Stick with what you’ll actually open every day. Don’t be afraid to quit a tool when it stops helping. Writing is about getting words down. The right tool is the one you’ll use.
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