Artificial intelligence is taking the consulting industry by storm – is that a cause for concern?

Artificial intelligence (AI) has long been within the highlight. But the talk about whether it’s a “Shortcut to utopia“ or possible harbinger of the top of the world.

Meanwhile, one group has quickly jumped on the technology and all of the hype – consulting firms. And they’ve large expenses.

lawyers of technology are ushering in a brand new era of skilled efficiency for consultants. Emails, presentations and reports that were once tedious can now be accomplished in a snap.

Many consulting firms have already took the chance to supply other corporations with skilled advice on the way to profit from latest generative AI tools.

So why does the consulting industry see such transformative potential – and is it an excellent idea to rush headlong into this technology?

Wait, what do consultants do?

The consulting industry is notoriously shrouded in mysticismalthough they usually received large orders from governments and enormous corporations.

Simply put, consultants are about providing their clients with expert advice and solutions that help them improve their performance, solve problems and achieve specific goals.

They often have specialist knowledge, skills or experience that’s relevant to a selected client, so the character of their work can vary considerably.

Clients often seek consulting services because they need assistance solving problems and making decisions for a selected project, or because they need external validation of their decisions and want an independent report.

Numerous skilled services firms offer consulting services, including the “big 4”: Deloitte, PricewaterhouseCoopers (PwC), Ernst & Young (EY) and KPMG.

There are also many specialized consulting firms, including McKinsey, Bain & Company, Boston Consulting Group, Kearney and LEK Consulting.

The demand for consulting services is basically as a result of the increasing complexity of doing business as a result of globalization, digitalization, changing regulations and plenty of other aspects.

However, growth within the Australian consulting sector is slowed down this 12 months amid the impact of the PwC tax scandal and sluggish economic growth.

How can AI help?

Artificial intelligence (AI) has been around in many alternative forms for a while. Until recently, nevertheless, it was mainly used internally by organizations and required specialized training. This modified with the general public introduction of “generative AI” models comparable to OpenAI’s ChatGPT.

These models differ from traditional AI of their ability to generate something latest, comparable to text that’s virtually indistinguishable from that written by humans, or other kinds of output comparable to images, videos, or sounds.

Large language models like ChatGPT were among the many first to offer most of the people a glimpse of what AI may very well be used for.

However, this also has concrete implications for consulting firms: the models can analyze large amounts of knowledge quickly and cost-effectively, thereby generating tailored feedback.

Because generative AI offers such efficient services for business evaluation and strategic planning, many potential clients may wonder if purchasing consulting services continues to be worthwhile in the long run – especially given the constant improvement of those technologies.

Always one step ahead

It should due to this fact come as no surprise that the consulting industry is investing heavily in generative AI. Just consider the massive 4.

Deloitte And EY have already used conversational AI assistants to extend worker productivity.

KPMG’s customized version of ChatGPT – KymChat – was launched in March to speed up the preparation of sales offers for consulting activities through the rapid identification of relevant experts.

In May, PwC OpenAIs largest corporate customer after purchasing greater than 100,000 licenses for the AI ​​giant's latest models.

Other players within the knowledge work sector are also touting the productivity-enhancing potential of generative AI for similar tasks.

The US financial giant JPMorgan Chase recently rolls its own large language model called LLM Suite, which it says can “do the work of a research analyst.”

What does this mean for the business model?

To fully realize the potential of this technology, corporations must use it effectively. This means providing their customers with a human-centered value proposition that goes beyond what technology alone can deliver.

Generative AI tools cannot replace the human trust that is usually critical to successful consulting, nor can they supply the depth of experience (and access to relevant human experts) that an experienced consultant can offer today.

But technology will simplify many on a regular basis tasks. It can even function a sounding board for decisions and business strategies and suggest solutions.

At least within the short term, corporations are more likely to use AI to “complement” human advisors slightly than replace them.

What are the risks?

The introduction of generative AI also poses risks for the consulting business.

A significant problem concerns creativity. Since the models generate their results based on past data, the range of potential solutions they’ll discover is at all times limited to their training data.

Over-reliance on the identical models could undermine the flexibility of consulting firms to innovate by diluting their clear competitive benefits and causing them to change into increasingly similar.

Such a phenomenon has already been observed in studies on the impact of generative AI on students' creativity.

My own research has shown that over-reliance on automation technologies comparable to generative AI can result in a loss of experience. In the long term, this effect can seriously damage the knowledge and popularity of organizations.

If younger consultants still in training outsource an excessive amount of of their considering and evaluation work to generative AI, they might fail to develop their very own analytical skills.

And after all, the technology itself isn’t perfect. Generative AI is understood to make mistakes and even “hallucinate,” meaning it makes things up entirely.

All of this underscores the importance of using generative AI properly, while keeping in mind the unique value that humans can bring.