5 Ways Generative AI is Redefining Profitability Across Industries

A Storm of Disruption

The business environment used to be very different: sluggish regulatory development, graduates willing to work 80 hours a week, every email to the client billable, and a handshake on the golf course was enough to secure million-dollar contracts. This world is disappearing. And companies that don’t adapt will soon be fighting for survival.

In fact, businesses are facing a storm of change:

• Regulations and laws are evolving faster and becoming more complex.
• Just like employees in other industries, workers are demanding more flexibility in how, when, and where they work. And they want to work smarter, not harder.
• Customers want more transparency about exactly what they’re paying for and why.
• Increasingly, these customers are also demanding that businesses compete for contracts, rather than sticking with providers they’ve worked with in the past.

These new realities are radically changing how a successful business must operate. Established large companies must now figure out how to overcome years or even decades of inertia, siloed operations, and analog processes. Meanwhile, fast-growing challengers have a unique opportunity to disrupt the market. To do this, they must position themselves as perfect strategic partners to meet their customers‘ future needs more efficiently, effectively, and transparently.

Despite (or perhaps because of) these challenges, businesses must protect and increase their profitability in the long term. So how should they respond to this „new world order“?

From Business to Enterprise

To survive and thrive, businesses must evolve into enterprises. This means they need to develop new capabilities, including:

• Improving their ability to cope with the rapidly changing and increasingly complex regulatory environment
• Offering flexible work practices and showing a genuine commitment to the well-being of their employees
• Moving away from time-based billing and towards value-based fees
• More proactively serving and managing client needs
• Skillfulness in competing for contracts against hungry, agile competitors

The first hurdle to overcome in realizing these new capabilities is an attitude issue. Leaders must be willing and able to overcome the „we’ve always done it this way“ mindset. That will be difficult enough for many. But they must also embrace new technologies whose capabilities even experts don’t yet fully understand.

One technology stands out in particular – generative artificial intelligence (AI). The advent of ChatGPT and other tools based on „Large Language Models“ means that AI is on everyone’s lips and no longer reserved for tech enthusiasts. And the service sector is one of the industries that will be most affected by this.

And not only that: Business leaders who think they have 5 or 10 years to adjust to generative AI are in for a shock. Because it’s no longer about preparing for it – it’s already here.

Businesses need to learn how to use it faster and more effectively than their competitors now. If they do, they will likely develop a significant and perhaps lasting competitive advantage. And many are already doing so.

Efficiency is Not the Whole Story

Most comments about AI and its impact on businesses focus on efficiency, i.e., speeding up workflows, automating time-consuming manual tasks, and entire process chains. These aspects of the impact of generative AI are valid and important. However, they are only a subset of the actual potential benefits and the ultimate goal of most businesses: to serve customers as profitably as possible.

The rest of this white paper outlines how generative AI can help businesses secure a more profitable future.

5 WAYS GENERATIVE AI IS REDEFINING BUSINESS PROFITABILITY

1. Reducing Costs

The most obvious lever for increasing profitability is cost reduction. This is where the quick wins lie. And generative AI has the potential to make a significant contribution to this.

For example, a Deloitte report from 2020 calculated that automating contract lifecycle management could reduce associated costs by 60% – and that was before the introduction of ChatGPT. Extrapolating AI-powered process automation to all other low-value, labor-intensive tasks related to business operations, the potential savings for any company can be substantial.

Specifically, costs can be reduced by:

a) Automating workflows: Generative AI tools can be used to automate a wide range of necessary but labor-intensive tasks. These include, for example: research and analysis, due diligence, document creation and management, communication, and invoicing. Automating these tasks means that companies will have to spend significantly less on manual labor.

b) Reducing errors: Human errors can cause unnecessary costs in any business. Errors in documentation and processes such as document creation or contract review can be particularly costly. Humans – even highly qualified and experienced professionals – can make mistakes due to fatigue, in high-pressure situations, or due to the sheer volume of documents they are dealing with. Generative AI tools can analyze huge amounts of content in minutes and accurately detect errors or even issue prompts and warnings in real-time as documents are being created.

c) Compliance: Due to the scope, speed, and complexity of regulatory changes, incorporating them into documentation and procedures is slow and expensive. For example, the EU passes at least 1,000 new regulations every year. AI tools can help automatically integrate compliance with new laws and regulations into documents on a large scale, eliminating a significant portion of manual work.

d) Reducing risk: Errors and failures to comply with regulations expose companies to significant direct costs such as fines and lawsuits, as well as indirect costs such as reputational damage. Using generative AI tools to minimize the likelihood of errors and omissions automatically reduces risk and potential financial consequences.

IMPORTANT NOTE: Cost reductions are generally the fastest way generative AI can help companies maintain and increase their profitability. However, it is also the least strategic and, by definition, limited – after all, there is little left to save without compromising customer service.

2. Expanding Capacity

The complexity and scope of work associated with business services have always been a brake on profitability due to capacity constraints. The new level of process automation enabled by generative AI has the potential to solve this and enable companies to expand their customer base.

a) Expanding client business and acquisition: As professionals and support staff spend less time on trivial, repetitive, and low-value tasks, they have more time to acquire more clients and work with them on more cases.

b) Higher-value work: By freeing up capacity for low-value work, more resources are available for redistribution to higher-value and higher-paid work. This is one of the key drivers that will increase the profitability of businesses in the long run.

c) Dynamism and innovation: With more time available, professionals have more capacity to serve their customers more proactively and create added value in new ways. This could mean cross- and upselling within customer organizations. But it could also mean that entirely new services can be offered (see next section).

3. Strong Differentiation

Differentiation is an important value driver for any business. Companies can use generative AI tools to achieve this in various ways. Most of these can be defined as improved service quality or innovation.

a) Improved service quality: This can include, for example:

• Higher quality of documentation with fewer errors
• Faster response times to inquiries or customer communications
• Higher quality of customer communication in terms of accuracy and completeness
• Faster case processing
• More proactive management and development of customer relationships
• More robust security practices that foster customer trust

b) Service innovation: This can include, for example:

• Better and more diverse scenario modeling
• More accurate prediction of profit/loss analyses
• Improving the speed and accuracy of conflict warnings
• More creative solutions to complex problems
• Predicting future needs and potential risks of customers
• Demonstrating the ROI of services through more transparent linking of work to customer business outcomes
• Stronger positioning as a strategic partner rather than just a service provider
• Customized services for individual clients
• Development of internal AI-powered tools such as chatbots and virtual assistants tailored to specific customer needs

4. Attracting and Retaining Top Talent

The so-called „War for Talent“ is real, not only in terms of recruiting the best employees but also when it comes to offering them the most attractive working environment. Both established and aspiring professionals expect an efficient, flexible working environment. They also expect access to the best digital tools to help them work efficiently and effectively.

Young professionals are increasingly less willing to work the 80-hour week that was previously expected of newcomers. Therefore, the automation of time-consuming, labor-intensive manual work through generative AI is particularly important. But they also want the flexibility to work from anywhere during and outside normal office hours, making mobile access to digital tools an important prerequisite.

The automation of workflows also allows them to fulfill another important need – spending more time on enjoyable, challenging, and high-value tasks that directly contribute to optimal outcomes for the client. Generative AI tools can help professionals achieve all of this while reducing stress by saving them time and reducing the risk of errors that can easily happen under high workload and time pressure. A more fulfilled and less stressed professional is likely to be more satisfied, perform better, and be less inclined to leave the company when they receive an attractive offer from a competitor.

All these factors suggest that in the coming years, the more effective use of generative AI tools will be a key weapon in the war for talent.

5. Improving Business Outcomes

Ultimately, the profitability of businesses can be most effectively protected and increased by delivering the best possible outcomes to their clients. AI tools can help companies optimize these outcomes and achieve them more frequently. For example, if professionals can more accurately predict how likely a case is to be settled or go to court, they can give their clients the best advice.

AI tools can access and analyze a much larger amount of information much faster than would be possible through manual work alone. By combining these capabilities with value-oriented fees, professionals can justify higher rates because they deliver a better outcome. This is another important factor for the long-term profitability of businesses.

Better business outcomes are also a consequence of the other improvements enabled by AI that have been described in this document: Faster and more accurate research; more comprehensive investigations and due diligence; better case analyses and predictions; the rapid and accurate identification of errors or anomalies in documents and processes; improved capacity to focus on strategies and innovative solutions; improved customer service and communication enabled by AI-powered in-house tools.

Warning: Always Read the Fine Print

Generative AI is ushering in a technological, economic, and social change that may be more dramatic than that triggered by the Internet.

Futurist and author Ray Kurzweil said in 2020: „Artificial intelligence will reach human levels by around 2029. Follow that out further to, say, 2045, we will have multiplied the intelligence, the human biological machine intelligence of our civilization a billion-fold.“

In the field of business services, generative AI can be a revolutionary technology with which companies can reinvent themselves and the services they offer – as will be the case in almost all other industries. However, it must be understood that with the introduction of any new technology, especially one as powerful as AI, comes a host of risks, uncertainties, and unanswered questions. These risks include (but are not limited to):

• Privacy/Confidentiality: What will prevent AI tools from illegally collecting confidential data from customers, plaintiffs, defendants, and other parties?
• Increasing AI-specific regulation: To what extent, how quickly, and how effectively will the use of AI tools and the results achieved with them be regulated?
• Quality of inputs: How can professionals be trained to use tools effectively and avoid incorrect or potentially harmful results?
• Generative AI „hallucinations“: How can persistent erroneous results or so-called „hallucinations“ based on inaccurate or incomplete data be avoided and/or corrected?
• Liability: Who is liable if tasks completed or results delivered by AI tools are challenged in court? When and to what extent will AI be allowed to make decisions without recourse to a human professional?
• Creation, confirmation, and exacerbation of prejudices: How can the biases inherent in the human-created content that AI tools currently rely on be recognized and taken into account?
• Copyright infringement: How can potential copyright issues be avoided or identified before they lead to legal obligations for businesses and their customers?

Conclusion

Current generative AI tools do not „think“. They formulate coherent answers to questions based on the inputs provided and the information made available to them. And they do this many times faster than a human could. This means that tasks that would otherwise require a high proportion of manual work and/or those that do not require high intellectual skills are particularly suitable for automation. But the results they deliver are only as good as the data and other inputs they use.

Nowadays, AI tools in the provision of business services enable a complement and improvement, but not a complete replacement of human experience and expertise. Therefore, the results of any task delegated to a generative AI tool still need to be monitored and checked for accuracy by humans today.

Theoretically, this may soon no longer be necessary. After all, the technology and the quality of the results it delivers are improving at an exponential rate. It remains to be seen to what extent regulations and (ironically) court proceedings will slow down the practical application of what is technically possible in the legal field.

Nevertheless, the use of generative AI is as much a strategic imperative for businesses as it is for any other company – especially when it comes to maintaining and increasing profitability. And the rapid development of AI technologies means that there is literally no time to lose. Companies must now allocate resources to explore and leverage the possibilities of AI in their business.

The reason for this: Companies that engage with AI early on can gain a significant competitive advantage. If they use this advantage effectively, it will likely grow exponentially as the capabilities of AI technology also evolve.

The „robot professional“ is probably still a long way off, but businesses that don’t leverage the possibilities of AI sooner rather than later risk irrelevance and elimination. After all, ignorance is no defense in court – and it won’t save your business either.

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