Consulting is a phenomena brought about by the changing landscape of businesses. If you look back at the history for the greatest booms in any industries, it is always followed by a strong consulting firms building a robust frameworks to sustain the boom or growth.
I like to look at consulting business as a form or expertise that allows the knowledge to be applied across multiple industries to gain more insights & uniform growth.
The modern tech industry has managed to give a bad rep to the word ‘Growth’ as if it is a bad thing to chase growth. Ultimately every product and services organizations wants to achieve their goals and the successful ones invariably are very clear about their goals and priorities. They are willing to experiment to achieve it as well.
Talk about experimentation in the world of technology, there is no way for us to escape from the word popular today, AI. It is everywhere and everyone wants to be part of it. I am intrigued about it as well and knowing that I deal in data, I intend to look beyond the smoke & mirror of the buzzwords.
I am interested to shed some light about using AI in consulting business and not just using GenAI to write robotic emails and presentations but going beyond and using it into end to end processes and building workflows.
Before we dive deep into it, let’s have a look at traditional consulting models.
Traditional Consulting Model
There are roughly six types of consulting businesses -
- Strategy
- Management
- Operations
- Finance
- HR
- IT
Each of these consulting types target a specific area from business models to people and technology. The common factor in each of them is the standardized way of doing things and finding patterns that can be turned into models applicable across industries. The traditional consulting frameworks are designed to assess and measure the effectiveness of a business.
Any consulting firm will assess the organization in question within the factors of Internal and External influences.
Internal influences are typical to the structure of the organization and its efficiency, finding ways to measure it and building towards an optimal solution.
Some of the popular frameworks in place for evaluating an organization are -
- McKisney 7S
- BCG Growth-Share Matrix
- The 4P’s
- Cost vs Benefit
- Qualitative vs Quantitative
External influences are measured against the market standard and competitors against the standing of the firm under question.
Some of the frameworks have been in place for a long time like -
- PEST analysis
- Porter’s Five Forces
- Benchmarking
These can be used to evaluate the position of the organization against the market and competitors.
The common output for each one of these framework is development of value proposition for the organization to maintain a sustainable growth within the risk parameters. There is margin for error as consulting - internal or external is heavily dependent on people and the tools that they use. I will get to the problems and solutions but before that lets define the Value Proposition in Consulting.
The Value Proposition in Consulting
Value Proposition is the way the clients get to see the first impressions of your consulting business. While creating value proposition of your consulting business, take the liberty to brag about the theology, effort, throw statistics and vow to dazzle the interested party.
As a business owner, it is my job to clearly communicate what my business is about and how it will add value to the clients' business. If I can't clearly elaborate my own expertise, it will not bode well to convince the client about my value to them and their business.
Keeping the above definition in mind, it is highly likely that the value proposition should be a reflection of my personality, beliefs and value system projected onto the client, hoping that the frequencies match.
It is tempting to decipher the above problem statement into simple framework-
- Who
- What Problem
- What Solution
- Why
It is that much more tempting to construct this framework with a problem statement and feed it into ChatGPT, Claude, Deepseek or any other AI Agent for a quick answer. I am sure it will do a brilliant job of deconstructing the problem by providing answer to each of these questions.
It is also most likely that every other consulting agency will be doing the same thing and for a client who is shopping for the ideal fit will have come across these AI Agent generated pitch decks.
As far as AI is concerned, it has come across this problem statement before, the framework is fed into its learning and all it has to do is adapt to the language and tone of the question & voila, here's the smartness of AI at display.
As a consultancy, ask yourself this question - Who is asking for these generic AI generated solutions? The answer to this question will probably shed some light on the demands and ways of using AI in consulting business.
Who is demanding AI in Consulting Business?
AI is a tool to automate our workflows and solutions to reduce the time taken to bring the solution to the market.
It is not a tool to be used to create out of the box solutions that are generic in nature and just 'Get the Job Done'. If such solutions could hold water then clients had enough resources to fashion something on their own, after all they pay good money to consulting businesses for solutions.
Whenever a new product is launched in the market, the advertisements are always out of sorts and viral to the point of ridiculousness. It is exactly the same thing with these AI solutions. We are being pushed towards using one product for all the purposes, all the while being promised to us that more we use it the better it will be at the job. If there is one thing I have learnt in my 15 years of working in software industry, the job doesn't get easy just coz I have done something similar in the past. I might have a good head start into solving the problem, based on my experience but very rarely it has happened that one solution fits all
The question here is where, when and how should I use AI in the problem solving process for clients? The answer is in the nuance that a good consultant has developed working over the years solving countless problems for the businesses.
Best ways of integrating AI in Consulting
A most prominent question to ask regarding AI in consulting business is How to integrate AI agents in the business processes in most ethical way?
The popularity of AI in the Tech and other industries makes for a very trigger happy executive & management circles in an effort to acquire quick gains. Though it is not a bad thought, there are long term implications, known and unknown that the Data Science community have been raising alarms over but gets drown in chasing growth and quick wins. May be, for once listen to the Data Engineering Team and consider the alarm bells. Not to sound all doom & gloom but there are very real use cases for AI to iron the processes & workflows in consulting businesses.
Among the different facets of Consulting business, the important aspects are Data Gathering, Analytics & Automation.
To go a few levels deeper than the AI hype of the mainstream media, data gathering, cleaning and analysis has been cornerstone of efficient Machine Learning models and all of it is done with some easy to use python & SQL frameworks.
The enterprise models released from OpenAI, Anthropic, Deepseek, etc. can be easily accessed via API and used for creating integrated data engineering workflows to iteratively manage ETL workflows. These models can be used to make the technically complex work easy so the consultants can concentrate on providing business value to the clients by focusing on the strategy and creating value.
This works well into creating custom solutions using the Enterprise AI models that concentrate on solving specific business problems instead of some generic use.
Thus, consultants can actually provide easy quick wins to the clients and make it sustainable by turning the solutions into AI Agents using the Enterprise AI models.
Does it sound complicated and long winded way of saying that consultants needs to be AI Engineers or Data Engineers? Certainly not!
Infact, it is all about using AI models to quickly build demos and POCs to showcase the ideas in action.
If it still sounds a bit complicated, may be I can explain the way Etherion Consulting is trying to simplify the whole process.
How is Etherion Consulting tackling the popularity and ever increasing demand of AI?
I have been working as a consultant & contractor on understanding business problems, working on solutions and building automated workflows to improve efficiency for over 15 years.
Through the years, be it in large scale healthcare organization processing big data or working on process automation, there are always opportunities to automate the processes that are repetitive effort and over a period of time add to the cost and delivery time. An experienced consultant should be able to identify these gaps and opportunities and essentially task AI agents to automate these tasks.
At Etherion Consulting, data engineering and analytics sits at core of our solution oriented process, hence building efficient AI Agents to tackle such gaps in processes is utmost priority.
As we learn more from such integrated approach, there is room for consultants to have a continuous learning experience and spread the awareness. AI Agents can be leveraged to develop easy to understand tutorials and documentation to promote large scale adoption of such solution and approaches.
As AI Models continue to work in an integrated fashion, there is definitely a tendency for the models to self-learn and that can be used as an opportunity to improve the efficiency.
Sounds Great, right?
Well, there are ethical considerations to integrating AI into end to end process which cannot be ignored.
At Etherion, we look at the data in a holistic way and governance sits at the core of it. Let's dig a bit deeper into AI, Governance and Etherion's considerations.
Etherion, AI Agents & Ethical Considerations
Etherion Consulting is a Data Engineering & Analytics Consulting firm. Data Governance sits at core of data engineering with emphasis on data security, privacy and quality.
AI & Privacy sounds like anti-thesis of each other but they are certainly not and need to be considered alongside while working with custom solutions.
For any business, data is of utmost importance and in today's world it drives lot of decisions. To work with customer data needs to be handled as per the regulations. These regulations need to be embedded and enforceable from the infrastructure. There are tools that do a good job of it and I will cover about it in upcoming articles.
While working on custom solutions for our clients, Etherion Consulting is always looking ahead and with AI, there may be lot of unknown but we are always on top of the latest advancements and it is a major point of considerations in our solutions to make them scalable.
AI is a buzzword but the underlying work that has gone on for years is the major driving factor in Data Engineering & Analytics. Etherion looks to build on these fundamental concepts.
