AI First Steps: Finding the right use case for your organisation.

AI First Steps: Finding the right use case for your organisation.

We believe that customer research is the perfect first AI use case.

We believe that customer research is the perfect first AI use case.

Man calling behind his laptop
Man calling behind his laptop
Man calling behind his laptop
Photo of Greg Burke

Greg Burke

Published on:

May 21, 2024

Having arrived with a bang and no shortage of grand promises for the future of society, the hype around AI is finally starting to die down. So you might be surprised to hear that as a startup with AI at the core of our product: we’re delighted.

We’re delighted because we’re finally able to move beyond AI as a digital parlour trick, and get stuck into the real benefits it gives us today.

As talk turns to the strategic and competitive advantages that AI might bring, a lot of businesses are now asking themselves how to make a start with AI.

At first, integrating AI – a set of technologies that have only just become accessible to the mainstream – might seem like a daunting task. After all, a responsible business has a few areas to consider:

  1. Organisational value – What concrete benefits could this bring to the company?

  2. Customer/Client value – What concrete benefits could this bring to the customer?

  3. Organisational impact – Whose roles are affected? What processes will change?

  4. Technical requirements – Can AI be integrated with existing systems? What resources will be required?

  5. Shareholder acceptance – Does this align with the goals of shareholders?

  6. Legality and ethics – Is this compliant with relevant data protection laws? Is it acceptable to wider society?

These points make a good checklist by which to evaluate AI use cases. In the Venn diagram of Added Value (points 1 and 2), Feasible (points 2 and 3), and Acceptable (points 4 and 5), our ideal use case sits at the intersection of all three areas.

Let’s look at a use case which is going to be off-putting to an organisation that’s considering the use of AI.

Say our organisation is proposing to introduce a CRM system with AI-driven features. It has the potential to bring huge value to the organisation, by speeding up the writing of replies to customers.

But does it bring value to customers? It might, if waiting time is reduced, but there are other, proven ways to reduce waiting time, like increasing team size. Apart from that, the quality of service might even be reduced, if the AI writing is less personal than the hand-written versions.

The organisational impact of changing a CRM system is huge, because it’s integral to so many business units, from customer service, to marketing, to merchandising and business intelligence. Training is essential, and roles may be impacted. The technical impact is also extremely significant, potentially requiring time from in-house and vendor developers.

Shareholder acceptance should not be underestimated: shareholders can be anxious around matters of financial impact. And finally, from a legal perspective, the considerable burden of data security and privacy compliance, combined with AI, may land with the organisation implementing the CRM system.

This is an example of an AI use case which, for the reasons above, is undeniably challenging for an organisation to implement. So how about a simpler, more isolated use case that still has potential for huge added value?

We believe that customer research is the perfect first AI use case – and obviously we’re going to be talking about Tellet specifically.

The value to the organisation is that of fast, inexpensive and detailed customer insights, which is to say, extremely high value. The value to the customer is also present: a company which understands and responds to the needs of its customer, serves its customer better.

As a SaaS platform dedicated to research, Tellet’s organisational and technical impact is minimal. It’s designed to be used by existing insights teams, and training takes hours, not days. And since it’s hosted by us – your IT team and developers never have to see a ticket.

We have real-world experience of this: A major financial institution that is very hesitant in experimenting with AI chose Tellet for one of their experiments, as it could be done outside of their systems, by a small group of people within the organisation.

Shareholders stay happy, as the financial impact is extremely low. And finally – legal and ethical considerations. Tellet is built from the ground up to keep external participants’ data secure, and private in accordance with GDPR. In fact, we’re just putting the finishing touches on ISO 27001 certification. Ethically-speaking, we’re committed to keep participants in the loop: they always know that they’re speaking to AI.

In these ways, Tellet for customer research is a low impact, high value choice for bringing the benefits of AI to your organisation.

I’m Greg and I’m the co-founder of a new kind of research platform called Tellet. We use AI to conduct and analyse consumer research interviews for faster, deeper and more affordable insights.

Want a free trial? Book a demo with us, or drop me an email – greg@tellet.ai.

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