Beyond Efficiency: Driving Growth with GenAI

Large language models (LLMs) are transforming financial services and other regulated industries. So far, the focus has been on efficiency – streamlining workflows, reducing operational drag – and on insights, as firms use AI to analyze data, identify patterns and seize opportunities.

As early adopters of LLMs, financial services firms have used these versatile constructs to automate contracts, disclosures and regulatory reports; synthesize research across markets; and deploy internal copilots that support legal, compliance and operations teams.

Efficiencies drive real returns. One global bank cut time spent on compliance summaries in half using GPT-powered tools; bigger wins are on the horizon as more tools to automate and manage LLMs at scale hit the market. For the banking sector alone McKinsey estimates more than $200 billion in incremental value driven by generative AI.

While these sorts of activities are enormously important and impactful, they do raise the question why we are not seeing corresponding success stories on the growth side of the equation, particularly in sales and marketing organizations.

So instead of asking How do we save time? or How do we save labor? let’s challenge our LLMs to answer How do we grow?

Deployed in alignment with firmwide growth initiatives, GenAI has the power to change the way you find, engage and convince customers and prospects. It can help businesses:

• Improve engagement with customers via stunningly relevant, personalized interactions at scale using customer data and AI

• Explore and test adjacent segments (customer profiles or industry verticals) with less upfront effort and risk

• Compress insight-to-action cycles across the sales and marketing process, accelerating conversion.

Let’s take a deeper dive into these three scenarios.

GenAI’s most transformative impact in revenue-focused teams comes from its ability to synthesize deep customer data into highly personalized and timely outreach. By pairing LLMs with rich internal datasets – transaction history, service interactions, segmentation models – sales and marketing teams can generate emails, proposals and outreach content that resonates with each individual’s unique needs, goals and preferences.

Imagine a world where every communication reflects the recipient’s investment style, recent behavior, and current market context. This level of relevance, scaled through AI, moves engagement from generic to genuinely consultative – building trust and improving conversion at every touchpoint.

In other words: Exactly what you’ve hoped for ever since you first heard of digital media.

One of the underused strengths of GenAI is its ability to monitor massive streams of structured and unstructured data – for example, customer activity, news about competitors, or industry trends – and surface “buying signals” in real time that marketers can then act on.

For example: Is a prospect newly in-market due to an executive change or funding round? Has a client’s portfolio drifted from their stated risk profile? Is a competitor sunsetting a product your firm can replace?

LLMs combined with monitoring tools can detect and flag these micro-signals automatically, prompting advisors or marketers to reach out exactly when the need arises. This insight-to-action compression creates an always-on go-to-market engine that feels less like selling, and more like timely, relevant assistance to the customer in need.

Every morsel of sales and marketing content – whitepapers, pitch decks, investment updates and other materials that are the bread and butter of any growth effort – must hit the mark on message, tone and regulatory alignment. GenAI can dramatically streamline the process of creating and ensuring high quality and maximum effectiveness, supporting internal teams and external partners with drafting, revising and customizing materials that are brand-consistent, compliance-ready and tuned to audience expectations.

This means less time waiting on content reviews and more time executing campaigns. AI can also learn from advisor feedback and high-performing assets (and learn what not to do from the low performers), helping continually refine the quality and impact of materials in circulation.

At scale, this results in a content engine that keeps up with strategy, adapts to fast-moving market conditions and supports every sales rep and marketer like a top-tier editor-in-residence.

A technology as transformative as genAI shouldn’t be confined to the back office. The bigger opportunity lies at the front – where relevance, speed and engagement drive business outcomes.

This isn’t about the cold efficiency of automation replacing human endeavor. It’s about amplifying what your best people already know how to do – and doing it at scale.

Efficiency is expected. Growth is strategic. GenAI will unlock both – if you let it.