By Andy Jackson

AI technologies are developing exponentially! Making it all the more important to keep up to date with the ever-evolving suite of tools that offer capabilities across the whole organisation.

Mastery of generative AI and LLMs will lead to significant competitive advantages, through the ability to harness powerful insights, automate complex tasks, and foster creative solutions at scale. As these technologies continue to evolve, they will shape the future of industries, making it imperative for leaders to stay informed and agile in integrating AI strategies into your business models.

In this edition, three members of our amazing team delve into the transformative power of Generative AI and Large Language Models (LLMs). Ellie explores how to increase productivity with LLMs and ChatGPT; Mark digs into the world of GenAI and Anwesha introduces how AI is launching a new era in analytics.

And first up is …

CEO playbook: How to increase productivity 400% with LLMs + ChatGPT

By Ellie Guy

Dear business leaders,

Welcome to the future of data-driven decision-making!

In this fast-paced digital era, harnessing the power of Large Language Models (LLMs) like ChatGPT can be a game-changer for your business. As a developer in this industry, I’ve witnessed first-hand how these technologies can unlock revenue opportunities and skyrocket productivity.

So what are LLMs?

LLMs, or Large Language Models, are a neat advancement in artificial intelligence technology. They are designed to understand and generate human-like text, making them a powerful tool for data analysis, content generation, and decision support.

As I’m sure you’ve heard by now, one of the leading LLMs in the field is ChatGPT. Trained on 570GB of data [], its capabilities have made it the go-to choice for anything from chatbots to academic research.

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A CEO’s Guide to Generative AI

By Mark Larsen

In November 2022, OpenAI unveiled ChatGPT-3.5, an innovative milestone so transformative that it recalibrated our anticipations about AI’s imminent role in daily life. Amassing a staggering 100 million users in just two months, it became the fastest growing app of all time.

As the tide of generative technologies surges, CEOs are tasked with harnessing its potential, optimising advantages while curtailing risks.

The Difference Between Generative AI and Traditional AI

Generative AI boasts versatility and creativity, allowing it to tackle diverse tasks and content generation effortlessly. In contrast, traditional AI operates within a more confined scope and requires greater configuration and expertise to solve specific problems.


Products and services that leverage existing foundational models often present the most straightforward opportunities for revenue and lead generation.

Consider the following:

  • WonderPlan automates holiday itineraries.
  • Recently trending, BarbieMe turns users into a doll.

Author as a doll

These applications cleverly harness existing models, tailoring them in ways that resonate with their intended audience. This is low effort, high reward when done well.

Generative AI predominantly emerges in an open, collaborative environment, with APIs being widely available. This means barriers to entry are surprisingly low.

If you have an idea but you’re unsure how to get started, reach out. Our Data Cubed experts will know the simplest way to bring your ideas to fruition.

Read Mark’s full blog here:

AI Ready Leadership: Understanding data maturity for competitive advantage

Integrating AI with your business is vital to keep up with the times. But, in order to do this successfully, it’s important to ensure your data is ready for it.

In our webinar, we dived into the steps of getting your data AI-ready, including our 6 pillars for data maturity:

  • Architecture
  • Governance
  • Analytics
  • Culture
  • Risk Management
  • Quality

Watch the full webinar below:

A new era: AI for analytics

By Anwesha Pattnayak

Artificial intelligence is augmenting the entire analytics lifecycle. AI can deliver deeper, more meaningful insights, provide natural language interaction and automate manual process by making use of innovative capabilities such as machine learning, large language models like OpenAI’s ChatGPT etc.

What is Data Analytics?

It involves the examination of raw data to extract valuable and actionable insights. This practice falls under the umbrella of business intelligence.

What is Artificial Intelligence?

Artificial intelligence is a technology designed to imitate the human mind, particularly in areas such as analysis and learning. It is designed to understand concepts, draw conclusions on data, become self-learning and even interact with humans. AI systems work by ingesting large amount of labelled training data, analysing the data for correlations and patterns, and using these patterns to make predictions about future states.

How AI changes analytics

AI-driven software has the capability to autonomously analyse data from its source and provide valuable insights. Employing AI-guided systems in your data operations allows for the automatic cleansing, analysis, interpretation, and visualisation of data.

Benefits of AI-driven Analytics

  • Greater Productivity.
  • Pattern Recognition.
  • Flexibility.

Challenges with AI-driven analytics

  • Expensive.
  • Prone to Error.
  • Lack of Regulation in Some Sectors.

You can read Anwesha’s full blog here:

Getting started with Generative AI in your business

Just in case you missed it, we held a webinar talking about how to unlock the possibilities of Generative AI for your business.

We gave some benefits of implementing AI across your business, but 5 simple steps to get you started.

You can watch the full webinar below:

Interested in learning more about how AI can be used in your organisation? We’re offering a FREE 2 hour Ideation workshop.

Get in touch at or visit our website at

Thank you for reading. We’ll be back soon with more data news next month.

Team DATA³