Rain check

Artificial intelligence (AI) is a constant presence in the news. Its ability to process vast amounts of data – far beyond human capabilities – is being harnessed by companies to streamline time-consuming administrative tasks, save resources and, where appropriate, reduce risk.

As the co-founder of a client management platform that leverages machine learning and augmented intelligence, I have been deeply engaged with the AI revolution that’s generated so much discussion in recent years. The real concern, or perhaps the most significant conversation, revolves around whether AI will take jobs. And not without reason – a recent study by Goldman Sachs suggested that 300 million jobs might be lost to automation across the European Union and the United States.

It’s fair to say that AI can identify trends in conversations and provide valuable feedback in client interactions, thus supporting communication. But the central question remains: can AI replicate tasks that require a distinctly human touch? Currently, there’s no evidence suggesting that machines can engage with clients, build relationships or create the trust and engagement that is essential in the legal profession. While AI offers numerous applications, this article explores where automation ends and soft skills begin.

Evolution of AI

To truly understand AI, it’s worth starting with its origins.

Alan Turing, a pioneer in computer science, proposed a method to evaluate whether a machine could exhibit intelligent behaviour indistinguishable from that of human being’s. Known as the Turing test, this method marks the birth of AI. Turing also envisioned machines capable of learning, reasoning and communicating in natural language.

Moving into the 1950s and 1960s, AI researchers developed systems to perform tasks like playing chess, proving theorems and translating languages. These early systems relied on symbolic logic and rule-based reasoning, requiring human programmers to provide explicit knowledge and instructions. Consequently, they struggled with ambiguity and complexity, and couldn’t handle common sense or novel situations.

In the 1970s and 1980s, researchers explored alternative approaches, including neural networks, fuzzy logic, genetic algorithms and expert systems. These methods aimed to emulate human processes, allowing systems to learn from data and experience. This enabled more natural and intuitive forms of human–AI interaction, such as speech recognition, computer vision and natural language understanding. But, despite their promise, these systems faced challenges related to scalability, reliability and consistency.

The 1990s and 2000s saw significant advances in AI, with the advent of machine learning and deep learning. Using multiple layers of artificial neurons, deep learning allowed AI to learn complex patterns and features from vast amounts of data. This led to impressive achievements in image recognition, natural language generation and game planning, sometimes surpassing human capabilities. Deep learning also facilitated new methods of human–AI interaction, such as chatbots, recommendation systems and social robots. However, these advancements brought issues of bias and ethics to the forefront.

In the 2010s and 2020s, researchers continued to refine AI methods, addressing both the opportunities and the risks associated with human–AI interaction.

Balancing AI and human touch

We will now delve into the intersection of AI and the human touch in client and prospect management. This topic is gaining traction across various fields, not just in law, as technology continues to advance.

• On one hand, AI excels at handling tasks quickly and efficiently. It can answer questions around the clock, resolve simple queries and manage multiple customers simultaneously. This can be a significant advantage for any practice, saving both time and money.
• On the other hand, we have the irreplaceable human touch. This encompasses the personal connection and rapport that professionals must establish with their clients and prospects – something AI cannot truly replicate.

So, what exactly is beyond AI’s reach? First and foremost, empathy. Humans have the unique ability to understand emotions, think creatively and offer a personalised approach that AI simply cannot match. As we look to the future the question arises: is the human touch in business development still as valuable, or is AI taking over?

Building better relationships

Recently, industry giants like OpenAI and Google have announced that AI will become more empathetic and focused on building relationships. This shift is expected to help innovators create deeper engagement between people and AI.

Currently, this relationship remains transactional, centred around prompt communication. This dynamic is markedly different from the nuanced relationships between human beings, and falls short of generating the value we seek in meaningful interactions. To foster long-term, meaningful relationships between AI and people, we need to rethink the framework within which business development operates.

Effective rainmaking

Let’s explore the basic business development framework that rainmakers need to respect.

Understanding client engagement

We must first understand how client relationships form. They generally start from a conversation, which then becomes a contact. This contact must evolve into a connection. At the core of this process are empathy and anticipating needs, enabling us to engage and respond appropriately. Human relationships that generate rainmaking thrive on mutual interaction, common engagement and reciprocation, all built on past experiences.

Another important aspect of this framework is the knowledge that business development relationships are dynamic, not static. They require understanding and give-and-take from both sides to function effectively. As rainmakers, we must respect this. Consider also that the relationship will change over time; it can go from hot to warm to cold to hot, and switch from low maintenance to high maintenance.

Enabling effective communication

A key skill here is the ability to initiate conversations. The strategy is always to reference previous interactions (if they exist) and project genuine interest (where appropriate). This interest should be communicated in the right way, at the right time, with the right content. It is important to do so with clear goals, and, if referencing past communication, do it with clarity.

In professional services, concerns about privacy and professionalism are paramount. We need to project professionalism in a manner that differentiates us from other practitioners. This can be achieved by educating clients or prospective clients, sharing new information, reinforcing existing knowledge and demonstrating consistent competence. The way we do this, and at what level, will reinforce the impression we have made. This process builds trust and is a vital part of the business development framework.

The nature of communication within the relationship will shape its depth. Whether through texts, WhatsApp, LinkedIn messages, emails, business cards, websites or marketing messages, the content used must have the right style. To create deeper, more personal connections, we must move beyond non-personalised communication to establish distinction.

Cultivating the right balance between verbal and non-verbal communication is a valued ‘soft skill’. There’s a trend known as relationship degradation, where the quality of interactions diminishes over time – a lunch becomes a coffee date, which then becomes an online meeting, which then becomes a phone call and, finally, text messages. This ‘improvement’ in use of time, this drive for more for less, has created a rainmaking environment where our ‘best connection’ is now a target for an in-person conversation for a competing firm.

Face-to-face communication plays a part, too. Physical interactions bring in elements such as body language and tone of voice, which often outweigh what’s being said. Rainmakers need to know intuitively when to nudge a relationship forward, when to send a reminder and what type and style of reminder to send. They must be able to discern when a light-touch text or a meaningful conversation is the correct approach. This mirrors the care and attentiveness of a thoughtful friend, fostering a sense of connectivity and understanding.

Aligning your goals

Goal orientation of the two-party relationship is another critical component. To make a relationship function, we must be fully aligned with the other party’s goals; this includes their personal, commercial and career objectives. This alignment will allow the rainmaker to provide continuous support and motivation. Relationships are reinforced through purposeful, goal-driven interactions, which strengthen the bond between the parties involved.

Reciprocity is essential for effective rainmaking. Both parties must engage in meaningful exchanges of value, far beyond a simple thumbs-up online. Reciprocity builds trust and emotional bonds, making both parties genuinely invested in the relationship. We need to anticipate the other party’s needs, respond promptly and appropriately and actively participate in conversations that foster this. Many rainmakers believe the power of reciprocity trumps everything else. But what does fairness look like in terms of reciprocity? For this to work, both parties must intuitively know what is fair from the other party’s point of view.

Building on previous interactions

Then there is the importance of building on past interactions. In the realm of business development, the significance of past interactions cannot be overstated. Cultivating relationships hinges on the ability to build on previous encounters. It’s crucial to consistently advance these encounters in a manner that aligns with both parties’ interests.

By picking up from the right point, familiarity is fostered and trust is deepened. This mutual progression ensures that both parties are advancing the relationship at a harmonious pace, reinforcing the foundation for future collaboration.

Harnessing AI for rainmaking

This is actually a relatively short synopsis of the framework that developing clients and prospects falls under, and you have to ask yourself: how could AI work within this?

If these are the drivers for rainmaking and the communication strategies of business development, then the future of AI does not lie within this framework. The success of the framework, and how it differentiates two hardworking lawyers, hinges on personalisation, not generic interaction. To consider the use of AI in terms of winning and keeping work, we must therefore look outside this framework.

When it comes to business development, AI can still play a role. For example, it can automate basic contact strategies, recall past interactions and emphasise reciprocal exchanges. So, let’s explore where AI could make a difference.

• AI could improve access to our engagement strategy by identifying frequently asked questions about our services. AI tools can identify trends in these questions and feedback, helping us frame our communication more effectively.
• AI can enhance conversations, whether via text, email, online meetings or face-to-face interactions. By analysing large amounts of text and data, AI can extract valuable information about the client’s problems, providing meaningful insights into their interests. This research feature ensures that even ‘small talk’ has added value, as AI can identify areas of interest.
• Personalisation is key. It sets professionals apart through tailored newsletters, specific communications, niche articles or bespoke messages. AI can determine the best way for a prospect or client to absorb information, whether through bullet points, short or long conversations, visuals or narratives. It can even create personas.
• AI technology can improve our customer duty communication. These advancements would free up time for busy lawyers, allowing them to focus on the framework of soft skills where they can truly make a difference in business development.

AI has a future within the profession, but rainmaking is a full-contact activity and will remain so for the foreseeable future.