All insights

There’s no denying AI’s impact on financial services. We are seeing firms set lofty ambitions and take great steps forward. At the end of the day, though, there’s often still a large gap between high-level strategic talk and tactical, day-to-day implementation.

For investment marketing content in particular, our clients have long spoken about wanting to implement AI for greater efficiency. Coming off years of constrained resources and reduced team sizes, these content marketers are yearning for a tool that can create greater bandwidth and efficiency in their roles, so they can then devote more time to strategic, truly human tasks – AI's supposed biggest benefit.

Yet, concerns remain:

  • How much does a human need to be “in the loop” if AI is involved in creating or editing content?
  • Where is AI better used to augment (i.e., accelerating tasks done by humans) and where can it fully automate (i.e., taking over formerly human-driven tasks)?
  • What is the risk versus the reward here? When do content quality or efficiency improvements with AI outweigh possible negative consequences?

Ultimately, your content represents the voice of your firm, and we operate in a highly traditional and regulated industry. Therefore, it’s wise to approach integrating AI into your content workflows with caution.

But expanded adoption must begin somewhere.

We see a few key use cases stand out as easy, near-term wins for investment marketing leaders to enhance their content efforts using AI:

1. Content research

The clearest near-term use case is probably one you may already be doing if you ever Googled something and only read the AI-generated summary or have ever asked ChatGPT to explain something to you – namely, simple research.

Large language models’ (LLM) clearest benefit to any user is their ability to compile information into a single, easy-to-digest format. An AI model can quickly summarize information in one view that may have required trawling through dozens of webpages as recently as two years ago.

LLMs then present an obvious tool for marketing writers needing to conduct research and understand concepts - to draft a blog or whitepaper or other piece of content.

Our recommendation here is not simply “tell your writers to use AI for research,” though.

Rather, teams must be upskilled in how to effectively and safely use AI for research. Public LLMs like ChatGPT and Perplexity are useful for explaining concepts or conducting public research, but every user needs to be “AI literate.”

AI outputs can often contain inaccuracies and biases, so one must understand how to spot these and ensure AI-driven research creates a stronger foundation for your own, human-driven writing – not the opposite.

And obviously, no confidential or proprietary information can be plugged into an LLM, or it risks being an input for the model’s ongoing training.

We, therefore, see firms pursuing their own internal, ringfenced GPTs (generated pre-trained transformers), where users can input company data with no security risk. This is an even bigger boost for investment content marketers, who may be able to then use an internal GPT to search past company content or plug in data for analysis.

Creating an internal GPT is a large task that sits far outside the scope of a marketing team – but if your firm already has one, and your marketing team is not yet fully leveraging it, it may be worth exploring how it can further benefit your content workflows.

2. Content translation

Investment content marketers may be responsible for, or interface with, those who localize and translate content for different regions.

We see many global firms exploring how AI tools can enhance content translation – it's a prime use case with clear near-term benefits. For the managers conducting translation services in-house, AI can streamline processes and reduce turnaround times, improving speed to market across all regions.

But, as with all AI adoption, it must be approached carefully, with strong human oversight and governance to ensure accuracy.

For managers that outsource translation services, whether to large providers, boutique agencies or freelancers, it may be worth exploring how their translators are adopting AI and using it to increase their own quality and efficiency.

3. Content repurposing

We believe AI is still many years away from being the driver of drafting content for our industry, particularly more editorial-style content. It can certainly enhance a writer’s own skill and efficiency. But, given AI’s current constraints, asking it to write a blog post or whitepaper for you is likely to create something lackluster, inaccurate, or even plagiarized.

One of the top early use cases we see for how AI can boost actual content creation, though, is in repurposing. This can mean many different things:

  • If your firm has a secure, internal GPT, paste in a blog and ask it to write 3-5 versions of LinkedIn copy. You can then revise and enhance it with your own expertise as needed.
  • Use a simple AI video maker to assist in repurposing a core content piece into a multimedia format. For example, Storyline AI can help wealth managers easily create video portfolio updates with engaging charts and visuals.
  • Integrated AI tools in design platforms like Canva can help a non-designer easily repurpose a graphic made for one channel into the size and specifications needed for another marketing channel.

Content marketers in our industry can reap major benefits from AI, even if it may feel unsettling at first. However, doing so requires not just high-level talk, but tactical implementation.

We’re happy to partner with your content team to understand your current AI maturity and the near-term use cases that make the most sense for your goals – reach out today to discuss more.