Human-AI synergies: the rise of the roboconsultants, the role of Human Intelligence and experts commentary [Series - Part II]
How consulting will inevitably change with the rise of the AI era (Part II)
In the previous part of this series, we introduced the AI-native consultant of the future: the roboconsultant.
This is how we defined them.
Roboconsultant: A highly skilled management consultant who is significantly augmented by advanced artificial intelligence tools and systems. This individual blends traditional consulting expertise with cutting-edge technological acumen, leveraging AI for enhanced data analysis, predictive insights, and innovative problem-solving. The roboconsultant operates at the intersection of human intellect and machine intelligence, redefining the boundaries of consulting efficiency, effectiveness, and creativity.
The roboconsultant is no Terminator or Robocop. The roboconsultant is a person.
Key characteristics of a roboconsultant
The roboconsultant will have to develop and master very specific features.
Hybrid expertise: combines deep domain knowledge in consulting and industry with proficiency in AI and digital technologies.
Data-driven insights: utilizes AI for sophisticated data analysis, offering more accurate and comprehensive insights to clients.
Innovative problem-solving: employs AI-driven tools for creative and effective problem-solving, particularly in complex and dynamic business environments.
Adaptive learning: continually adapts and learns new AI advancements and integrates them into consulting practices for continuous improvement.
Personalized client engagement: offers highly personalized consulting services, leveraging AI for tailored strategies and solutions.
Accessibility and scalability: democratizes high-level consulting capabilities, making them accessible to a wider range of clients, from large corporations to small businesses and startups.
Impact on the consulting profession
Roboconsultants will turn consulting upside-down, by providing services in ways and speeds that were never possible before:
Enhanced consulting services: elevates the standard of consulting services through more precise, efficient, and insightful solutions.
Career evolution and education: encourages consultants to continually evolve their skillsets, blending traditional consulting acumen with new technological proficiencies.
Market disruption and innovation: paves the way for innovative business models and engagement strategies in the consulting industry, potentially disrupting traditional practices.
Ethical and responsible use of AI: promotes a balanced approach to AI integration, ensuring ethical and responsible use of technology in consulting practices.
The roboconsultant is a paradigm shift in management consulting. It exemplifies an harmonious blend of human intelligence and artificial intelligence, both applied symbiotically to the consulting profession.
This new breed of consultant is poised to deliver unprecedented value, combining the nuanced understanding of human experience with the efficiency and precision of AI systems.
I strongly encourage you to read the previous part of this series, because it gives important context on what we are going to discuss next.
🚨 Today’s newsletter is not short.
Consider this entire series more of a dissertation or a small book rather than your typical newsletter.
You don’t have to read it all in one sitting.
I find that this length gives me the opportunity to chat about the various concepts related to the exploration of the Human/AI synergy in consulting we have embarked on last week.
Please find below a Table of Contents to summarize this issue.
Table of Contents
How AI is changing the consulting landscape
AI has been a tool in the arsenal of the consultant for quite some time.
This includes the use of Machine Learning algorithms, which are pivotal in analyzing vast datasets, identifying patterns, and making predictive analyses.
Generative AI, recently coming into the spotlight, has further expanded the toolkit. This advanced form of AI can create content, simulate scenarios, and generate data models that can be used for a variety of purposes, from developing marketing strategies to optimizing operational processes.
Natural Language Processing (NLP) has been, and still is, used to analyze textual data, extract insights from unstructured data like customer feedback, and enhance interactions with AI-driven chatbots or virtual assistants.
Finally, simulation tools and scenario modeling are used to forecast outcomes under various conditions, aiding in strategic planning and decision-making.
The impact of AI on the consulting landscape is multifaceted and transformative.
Here, I want to briefly explore the specific ways in which AI is driving change and innovation in consulting practices:
Data-driven insights: AI equips consultants with the ability to extract actionable insights from vast datasets. This data-centric approach enables consultants to make informed decisions, identify opportunities and threats, and develop strategies based on empirical evidence.
Automation of routine tasks: AI-driven automation streamlines routine tasks such as data collection, report generation, and data analysis. Consultants can dedicate more time to strategic thinking, client interactions, and value-added activities.
Hyper-personalization of services: AI allows consultants to offer highly personalized services. By analyzing client data, preferences, and behavior, consultants can tailor recommendations and strategies to meet the unique needs of each client, enhancing client satisfaction and outcomes.
Enhanced risk management: AI’s predictive capabilities enable consultants to identify and mitigate risks proactively. Whether it’s financial risk, market volatility, or supply chain disruptions, AI helps consultants anticipate challenges and develop risk management strategies.
Improved decision support: Consultants can rely on AI-powered decision support systems to evaluate multiple scenarios, perform sensitivity analysis, and make recommendations based on quantitative models. This aids clients in making informed decisions with confidence.
Throughout my career, I have seen AI applied to business optimization in many different ways.
Without violating confidentiality, here is a short (non-comprehensive) list of projects I have witnessed happening that leveraged Artificial Intelligence in some form.
Predictive Analytics for supply chain optimization
A global logistics firm employs predictive analytics to optimize clients’ supply chains. By analyzing historical data, their proprietary machine learning models forecast demand fluctuations, enabling clients to adjust inventory levels and distribution strategies in real-time, reducing costs and improving efficiency.
AI-enhanced customer engagement
The marketing department of a large enterprise uses AI-powered chatbots to enhance customer engagement. These chatbots provide personalized product recommendations and answer customer queries, plus collect data that it is then used to analyze customer interactions to refine marketing strategies. The result is increased customer satisfaction and higher conversion rates.
Risk assessment with Machine Learning
A large, global bank utilizes machine learning algorithms to assess investment risks. By analyzing market sentiment, economic indicators, and historical data, the bank provides clients with risk assessments and recommends portfolio adjustments, ensuring clients’ investments align with their risk tolerance and financial goals.
Data visualization for strategic insights
A niche strategy consulting firm employs AI-driven data visualization tools to create interactive dashboards for clients. These dashboards enable clients to explore data intuitively, identify market trends, and simulate scenarios, facilitating strategic decision-making and long-term planning.
Knowledge Management for quick access to expertise
A technology consulting company utilizes expert systems to manage domain-specific knowledge. Consultants can access a repository of best practices, technical documentation, and industry insights, ensuring they have the latest information at their fingertips to solve complex technical challenges efficiently.
These are examples of what has already been happening in, say, the last 10 years or so.
My hypothesis is that the increased speed of change in the next 10 years will be dangerous for most consulting firms out there.
Specifically, those who won’t adapt quickly and will not marry the idea of roboconsultants being at the center of their business, will either downsize drastically or disappear altogether (via exhaustion of market share or acquisition).
The Human behind the Machine
Consulting as an industry will not disappear. Consulting as we know it will.
As I like to say, the roboconsultant isn’t some sort of Terminator. Roboconsultants are people, just augmented by machines more prominently than anything else we’ve seen so far.
It is therefore a useful exercise to dive into the essence of human intelligence and its role in the successful integration of AI in a roboconsulting practice.
While AI systems excel in processing vast amounts of data and identifying patterns, they lack the nuanced comprehension and adaptable reasoning inherent in human cognition.
Here, we explore the dimensions of Human Intelligence (HI) that Artificial Intelligence (AI) cannot replicate, and how these dimensions are instrumental in roboconsulting.
The unmatched capacities of human intelligence
Unlike AI, humans possess the ability to empathize and connect on an emotional level. This emotional depth is invaluable in understanding client needs, motivations, and concerns, enabling consultants to tailor their approach effectively.
Human consultants excel in contextual understanding and creative problem-solving.
Humans can interpret complex scenarios beyond raw data, considering cultural, social, and economic factors that AI might overlook.
Humans have the innate ability to adapt their thinking based on new information, intuitive insights, and unstructured data. This adaptability is key in dynamic business environments, where variables and uncertainties are constant.
By combining human insight with AI’s analytical power, consultants can achieve a more holistic understanding of problems. This synergy leads to innovative solutions that are both data-driven and human-centric. In instances where AI may provide inconclusive or ambiguous results, human consultants can step in to interpret, contextualize, and make informed judgments.
This human intervention is essential in ensuring the reliability and applicability of AI-generated insights.
As we as professionals journey further into the era of AI-enhanced consulting, the value of human intelligence will become more apparent, and will explain why I don’t buy the doomers’ perspective postulating that “all jobs will be lost”.
The role of Emotional Intelligence in roboconsulting
In traditional consulting, we all understand the importance of Emotional Intelligence (EI) in landing clients, creating alliances, and delivering our messages to senior stakeholders.
With roboconsulting, the role of EI emerges as a cornerstone of successful client engagement and decision-making even more prominently.
EI encompasses self-awareness, empathy, social skills, self-regulation, and motivation (amongst other talents and skills).
In consulting, these skills translate into an ability to connect with clients, understand their emotional and business needs, and navigate complex interpersonal dynamics.
While AI excels in data processing, EI provides the human touch necessary to interpret and apply insights in a way that resonates with clients. This synergy enhances client relationships and aids trust-building, which is the foundation of successful consulting engagements.
Consultants with high EI can better gauge client reactions and adjust their approach accordingly. This sensitivity is key in building rapport, managing expectations, and guiding clients through change.
Emotional intelligence also plays a pivotal role in internal team dynamics.
It aids in resolving conflicts, promoting a collaborative environment, and ensuring effective communication, all of which are essential in managing AI-driven projects.
While AI provides data-driven insights, EI guides the application of these insights in a human-centric manner.
Consultants with high EI can factor in the emotional and human elements of business problems, leading to more comprehensive and sustainable solutions.
Needless to say, Emotional Intelligence is also critical in navigating the ethical dimensions of AI in consulting. Understanding the human impact of decisions ensures that solutions are empathetic and morally sound.
How to leverage intuition
You must have heard that, if you keep honing your consulting craft for some time, you develop a gut feel. Intuition.
But what’s intuition? How could we define it, in the context of our broader discussion?
At its core, intuition is the ability to understand or know something immediately, based on feelings rather than facts. In the consulting world, it’s about making swift, informed decisions based on experience and tacit knowledge.
Intuition has often a key role in decision-making.
It allows consultants to “read between the lines”, recognize patterns, and anticipate outcomes in ways that AI alone cannot. Intuitive thinking often allows for quicker decision-making, which is undoubtedly an asset in the fast-moving market environments we all routinely witness (pandemics, financial crises, layoffs, etc anyone?!).
Intuitive thinking enables consultants to make prompt judgments when data is incomplete or unavailable.
Intuition is a gateway to creativity, essential for out-of-the-box thinking. It can lead to innovative approaches in strategy formulation, where data alone might suggest conventional paths.
A key skill roboconsultants will need to develop is the usage of analytical data to ground their intuitive leaps. For instance, when a consultant might have a hunch about a market trend, data can validate this intuition or provide a reality check.
In scenarios where data is incomplete, ambiguous, or hardly “interpretable”, intuitive thinking can fill gaps, offering a more comprehensive view. It allows consultants to make educated guesses based on experience and contextual understanding.
Roboconsultants must become adept at recognizing the limitations of AI analyses, and understanding where and when to question or delve deeper into AI findings.
It can often take years, or decades, of work to develop such “gut feel”.
But it’s there that the value of consultants can be found.
Developing and cultivating important “soft skills”
Emotional Intelligence and intuition are known as “soft skills” however (let’s not be fooled by terminology), as we often say around here, people call them “soft skills” but soft skills are hard as rock!
Developing soft skills can be more challenging than hard skills due to their inherently abstract and deeply personal nature. Soft skills - in that post I linked above I call them “appreciating skills”, but that’s another story - are closely tied to an individual’s personality and behavior patterns. Unlike hard skills, which often have straightforward learning paths and objective measures of proficiency, soft skills are less tangible and harder to quantify.
For instance, learning a programming language involves following structured guidelines and practicing specific tasks until proficiency is achieved. In contrast, improving communication requires introspective understanding of your own behavior, emotions, and thought processes. That’s hard!
Moreover, the development of soft skills often requires ongoing adaptation and refinement. As your professional and personal environments change, the way these skills are applied and understood must evolve.
This continuous process of learning and adapting adds to the complexity of developing soft skills.
Lastly, the subjective nature of soft skills means that their assessment can vary greatly depending on context and observer. What constitutes effective leadership or teamwork in one situation might be different in another. This subjectivity makes it challenging to receive consistent feedback and to gauge improvement accurately.
So, how do we go about it when we realize that these are such important skills, bound to become even more important in the age of roboconsulting? What are some strategies and practices for consultants to enhance their emotional intelligence and intuition?
Leadership plays a fundamental role in cultivating what I define an emotionally intelligent and highly intuitive consulting practice.
Leaders can set the tone by modeling behaviors, providing training opportunities, and creating an environment that values and encourages emotional understanding.
Largely, the suggestions I am going to give in the next few paragraphs will be applicable to both Emotional Intelligence and Intuition building skills.
With a few tweaks, we could even envision applying the same ideas to other soft skills more broadly.
How to train for Emotional Intelligence and intuition
Fundamentally, roboconsultants need to develop and refine their Emotional Intelligence to ensure they can effectively bridge the gap between technological sophistication and human-centered service.
As we said, at the heart of EI in consulting is the ability to cultivate trust.
In a landscape where AI plays a central role, clients might feel alienated by the complexity and impersonal nature of technology. The role of the roboconsultant, therefore, is to humanize this experience, making clients feel understood, valued, and genuinely cared for.
Personalized communication stands as a key aspect of EI. This entails avoiding jargon and simplifying technical language. It includes tailoring conversations to resonate with clients’ unique emotional landscapes and their comfort levels with AI. Consultants must actively tune into clients’ emotional cues and adjust their communication accordingly, ensuring clarity and connection.
Transparency and honesty go beyond just setting realistic expectations about AI’s capabilities. They involve acknowledging the emotional dimensions of clients’ decisions and the anxieties that come with AI-driven changes. A roboconsultant’s ability to openly discuss potential challenges and uncertainties helps in building an atmosphere of safety.
Active listening is elevated in this context. It becomes a tool to deeply understand clients’ concerns, aspirations, and underlying emotions.
Empathy and understanding are paramount. Demonstrating genuine empathy helps in navigating the unusual emotional space of clients, reassuring them that their unique challenges are being acknowledged and addressed in the roboconsulting process.
Remember: your clients are not proficient or particularly familiar with AI. You, the roboconsultant, are!
Reliability and consistency in interactions establish a consultant as a dependable figure. This consistency is foundational in assuring clients of the consultant’s commitment and capability in managing the AI aspects of their projects.
However, building trust in AI-driven solutions needs to extend to how roboconsultants demonstrate the value and relevance of their solutions. Roboconsultants should articulate how AI addresses clients’ specific emotional and business needs, leading to tangible benefits that clients can relate to and appreciate.
Involving clients in the AI process is also a significant aspect of EI.
This involvement could range from seeking input during the development of AI models to interpreting AI-driven insights together. Such collaborative efforts are useful to demystify AI and to empower clients, making them active participants in the solution process.
All of these are traits that need to be trained.
While some levels of Emotional Intelligence, intuition and other soft skills might be innate, they can be honed and improved upon.
Roboconsultants will have to cultivate theirs, through exercises such as reflective practices and scenario-based training.
Let me explain.
Reflective practices involve a conscious effort to ponder on your experiences, decisions, and actions. When a consultant reflects on projects, including successes and failures, they develop a nuanced understanding of various business contexts. Pre-mortems and post-mortems are anticipatory and retrospective techniques, respectively, used to analyze and learn from potential and actual outcomes of projects.
Pre-mortem and anticipatory reflection: before embarking on a project, roboconsultants might engage in a pre-mortem exercise, envisioning potential challenges and setbacks. This process requires and supports skills like critical thinking and strategic foresight. By anticipating what could go wrong, a consultant practices empathy (understanding client concerns), communication (articulating potential issues), and problem-solving. This anticipatory reflection helps in honing these soft skills in a contextual and practical manner.
Post-mortem and learnings: after a project’s completion, a roboconsultant conducts a post-mortem analysis to understand what worked well and what didn’t. This exercise is rooted in reflective learning, through which consultants develop a more nuanced understanding of various business contexts and their own performance. It’s an opportunity to critically assess their soft skills like teamwork, adaptability, and leadership in action. This reflection is not about what they did, but how they did it: how they communicated, collaborated, adapted, and led.
Scenario-based training equips consultants to navigate unpredictable business landscapes. In such training, consultants are exposed to a variety of simulated business situations, ranging from market disruptions to organizational change. These simulations, powered by AI to reflect real-world complexities, require consultants to think on their feet, drawing on both their analytical skills and intuition. As they navigate through these scenarios, they learn to recognize patterns, understand subtle nuances, and anticipate outcomes based on a blend of data analysis and (the infamous) gut feeling.
I will give you an example.
Market disruption and rapid response scenario: in this scenario-based training, roboconsultants are presented with a simulated market disruption, such as a sudden technological breakthrough by a competitor. The AI component of the training generates real-time data and market analyses, simulating the business landscape. Roboconsultants must use this information to quickly develop a strategic response. They need to balance AI-provided market predictions and trend analyses with their own intuition about the client’s unique position and capabilities. This scenario teaches them to effectively blend AI-driven insights with human judgment to advise clients on navigating disruption and capitalizing on emerging opportunities.
This type of training is what we need in the upcoming era to form consultants who are expected to provide solutions that are efficient, empathetic and aligned with human values (not artificial ones).
Organizations must encourage environments where consultants feel empowered to trust their instincts, especially when they complement AI findings.
This can be achieved through regular knowledge-sharing sessions, workshops on emotional intelligence and cognitive biases, and encouraging a culture of open communication.
As consultants transition into the role of roboconsultants, their intuitive thinking becomes a distinctive competency that sets them apart.
An expert perspective
In our exploration of Human and AI synergies, we should not forget to look around us and understand what is already happening that is actively shaping the future we are envisioning here.
As an excellent complement to our discussion so far, today we have Tim and Joel from Discy (experts in the fields of AI and Management Consulting) joining this newsletter, to explain their vision, and what actions they are taking to help consultants build a practice that can thrive in the uncertain AI-driven future.
The more we discuss the trends and possibilities of AI… the more possibilities there seem to be!
One big question we keep running up against is:
What will it take for profound change to happen across consulting?
In what timeframe is that likely to happen?
Profound feels like a company no longer defaults to hiring an MBB or Big4.
“No one ever got fired for hiring McKinsey”.
Instead, they would hire a (newish) AI-native consultancy, or an AI to tackle that trickiest of 20% decisions.
Given the industry’s track record, it is difficult to see much beyond glacial change in the next 2 years. Over the next 5 - 10 years, we see a squiggly line of shifts that will profoundly change the industry (and delivery of consulting). Even if not so much the incumbents.
What are the emerging trends that will likely shape the consulting landscape in the coming years? What do consultants need to prepare for?
Here are several possibilities that will play out over the next 2 to 5 to 10 years.
AI… the new internet?
Every consultancy is testing how they use and sell AI services.
Some have built a value proposition around it. A small few will use it to power their value propositions.
In the short term, every project is an ‘AI project’. Akin to design thinking, customer experience, and sustainability before. Teams will know the buzzwords and every Exec summary will have a few sentences.
Eventually, these will become projects that take account of AI.
Meaningful, differentiated IP vs My LLM chat agent
Clients already use chat agents to spar over ideas, refine internal communications, and seek guidance. Their use will increase with familiarity and as companies deploy their own LLMs. Or public LLMs improve (and are accessible).
Consultants will need to compete against the average. Demonstrating the value of their proprietary IP and datasets to justify their advice or fast-track work.
Saying “we know you” or talking only of their people and approach won’t be enough.
A few boutiques seem well-placed here.
They know what IP makes them special, and can market and productize this. E.g., Baringa selling their climate change assessment solution.
Big firms grow stronger, Boutiques debate pathways
Bain, PwC, EY, etc. continue to channel their huge resources into making AI work for them. For now, this is chat agents to query their vast knowledge set.
Boutiques will test their options to not fall behind the curve.
Most lack the time, budget or volume of data to mimic the larger firms. Some will leverage an industry solution. Others will use AI to punch above their weight (e.g., Clarasys, Optima Partners).
The next wave of in-house transformation teams
In late ‘22, we interviewed 40+ people in senior in-house transformation & strategy roles. We learned their role had shifted.
From centralized watchdogs of corporate strategy and executors of strategic change. To more of a support and enablement role to business units to deliver change themselves.
The AI era will spur the next wave of building in-house knowledge. These teams will advise functional heads and leaders on how to plan for, resource, and drive AI changes in ways of working. To manage expectations, impart know-how, and reduce external spend.
Overseas incubators of AI-native consultancies
Indian SIs (TCS, Wipro, Infosys etc.,) have built well-renowned commodity consulting practices.
AI enables them to continue their evolution up the consulting services spectrum.
AI will help them pick up more low-value consulting work.
Generation, classification, and interpretation of unstructured data. Mid-to-long term it may help them incubate the first AI-native consultancies.
AI-native students join the workforce
Firms will welcome individuals accustomed to using AI in everything they do. Their expectations of the tools, and work they engage with will bring a different tension. Atop of the firm's current drive to motivate and train people to work well with AI. Itself a continuation of the drive to ‘be more digital’.
New joiners will enable or boost a firm’s offering.
Depending on where the firm opts to double down. E.g., Critical data analysis, and/ or Data science and/ or Deep AI.
Skills complemented by no-code skills and traditional ‘soft skills’.
What to prepare for?
We discuss several questions with consulting firms to help them prepare for AI’s possibilities. E.g., Threat of substitution, threat of declining relevance.
How can you extract more value from your firm’s collective knowledge (your most under-exploited asset)?
What is the most promising and accessible technique or tool you have to help your main customer base?
How can you productize and offer a service you frequently offer (which is thoroughly detailed and templated)?
How are you anticipating and staying ahead of changes in the expectations of your key clients?
Which workflows do you need to transform anyway (irrespective of AI) because they are manual and leave data everywhere?
Which tools and AI products can you use in your service delivery (that are best suited for management consulting)?
How are consulting roles evolving? What does the future entail for the collaborative nature of consulting teams that include both humans and AI?
For the foreseeable future, the purpose of a consultant will remain the same; Educate, advise and, support clients to make a decision and act upon it.
In achieving this, there will be more onus on the consultant to:
Help clients be more data-driven in their decision-making,
Deliver more tangible outputs and,
Operate to the speed and impact that clients expect.
Everyone can do data
Today, most projects need to answer the “AI potential/impact” question. So consultants will want to be able to ‘speak AI’ and understand the main terms. Incorporating the principles and language in the frameworks they use.
Consultants will also need to help reset expectations around what AI can achieve right now. Helping clients understand how they make decisions, and the best option to support this process (e.g., data analysis, data science, ML).
As LLMs and Chat agents improve, consultants can analyze more data, faster. Without a large expense or needing technical data science or ML expertise.
For now, it is more to learn the parameters for crafting effective prompts to retrieve data and test the quality and accuracy of the response.
Tangible (prototype) deliverables.
Consulting teams will increasingly be expected to deliver a “thing” as an output of their work. A prototype of a change/add-on, an interrogatable repository of the knowledge they've gathered, etc.
No-code/ low-code compounds the benefits of AI. Potentially making data science more accessible. And likewise, building digital products.
Rising pressure on cost & speed.
“Why am I paying for someone to do that manually??”.
Consultants will need to be literate and confident to deliver work that relies on AI. As well as to explain when they have and haven’t used AI.
Part of this will be educating the client on when they need an AI solution, vs solely analyzing the data vs carrying out statistics. Each of these requires different resource demands.
More time for what matters
AI gives the humans in consulting teams back time to reinvest in activities that add greater value to their clients. Namely, spending more time with the client and their stakeholders. Testing ideas, gaining support, and “winning hearts and minds” for the change.
Take the example of a discovery, diagnosis or assurance project.
Before: Teams repeatedly quote 30–40% of their time is spent collecting the notes and data from various interviews and source files. Identifying what is important in the data. They then consolidate it into one file (e.g., Excel). So they can theme and analyze the data (normally on a whiteboard, then back into Excel).
Now: Using AI (within a well-designed tool), the consulting team ‘outsources’ coding and organizing all the data gathered to the AI. Giving them a data set they can explore and query in minutes (instead of days).
This supports one important workflow for consultants. Other workflows will be transformed by other tools tailored to the needs of consultants.
The consultancies that truly evolve will use the next 2- 5 years to go beyond simply offering what clients expect; to profoundly shifting how they deliver work.
How are client expectations changing? What will clients demand from consulting firms in the future?
Clients often need to act with incomplete information. AI can give them more context to inform their decisions. Affording more self-sufficiency, and more nuanced use in where they use consultants.
E.g., A senior process transformation lead at a multinational telecom was able to avoid hiring a consulting team to run several workshops. Instead using ChatGPT to prepare slide content and test their argument.
AI will help clients scrutinize consulting proposals and deliverables. As well as spend decisions. This will impact the proposals they issue, the questions they ask, and the expectations they have for the work they contract. I.e., In the future, more clients will expect to see and experience tangible evidence that the consultant is applying their unique IP and insight to deliver the work.
Especially as companies grow more accustomed to using AI-powered solutions (e.g., Celonis, BusinessOptix) to perform more work in-house. This will catalyze more firms to sell their wisdom as productized solutions.
Another demand/ expectation from clients will be for more support in helping them be more data-driven in their decision-making.
83% of CEOs want their companies to be more data-driven.
Yet despite all their spend on quantitative BI tools, only 29% say they successfully connect analytics to action. Companies still need to hire consultants.
Especially as they are more awash than ever with qualitative data.
For profound change to occur across Consulting, there needs to be a change in both the capabilities of consulting firms and company buying habits. AI must empower emerging firms to be so much better they can’t be ignored, or inspire incumbents to fundamentally change how they operate.
Discy aims to be part of the solution. Enabling firms to be a step ahead of the status quo speed of change. Giving them a way to start to adopt AI truly. In a part of your work that makes a meaningful difference to your clients. This is without you needing to invest significant time or expense. Instead, dream big, and use Discy now to answer the first part of what being an AI-consultancy is.
🎉 Congratulations! You made it through Part II of the “Roboconsulting Series”.
If you are intrigued by the concept, I would be immensely grateful if you could share this with other friends and colleagues that might be interested in it.
I want to ask for your feedback, comments and ideas.
❓ What is roboconsulting for you? How might you implement it in your day-to-day professional activities?
🚨 CALL TO ACTION - I need your help
I have a small favor to ask you.
If you are, or personally know:
an AI leader (any industry)
an AI consultant (independent or not, but only if you have solid expertise)
a CEO of an AI-specialized company (any size)
a technology expert in AI-related disciplines
I would like to talk to you.
I am collecting opinions and perspectives from industry experts and thought leaders on the future of consulting in the age of roboconsulting.
Specifically, I am looking to chat to you about:
Emerging trends that will likely shape the consulting landscape in the coming years, providing insights into what consultants need to prepare for;
How consulting roles are evolving, emphasizing the collaborative nature of future consulting teams that include both humans and AI;
How client expectations are changing and what clients will demand from consulting firms in the future.
Please share this post with people that could be interested in talking, DM me on 𝕏 or email me directly.