Harnessing the Power of AI: How to transform your business

By hedgehog lab
22 Jun 2023

Contrary to the dystopian visions portrayed in sci-fi movies, AI is a remarkable tool that can enhance our capabilities and address the greatest challenges of our time.

We stand on the brink of a digital revolution, accompanied by substantial changes. Forward-thinking business leaders who desire a competitive edge over their peers embrace this transformation and the countless opportunities it brings. Particularly the transformative power of AI in driving innovation, fostering creativity, enabling collaboration, and enhancing interactivity for our clients.

The impact is undeniable, with top AI applications generating millions of pounds within months. Our clients are eager to explore how AI can benefit them, and we are here to provide guidance amidst the ever-evolving technological landscape.

Statistics paint a compelling picture of the AI revolution:

Now is the time to embrace AI’s potential, seize the competitive advantage, and navigate the dynamic world of technology with a trusted partner.

So, what is AI and what can it do?

Simply put, the term AI refers to computer systems developed to perform functions that usually need human intelligence. 

So, we’re talking about things from decision-making, problem-solving, language processing and speech to image recognition.

With AI, machines can learn from data and adapt their own behaviour. Think risk assessments and fraud detection, more accurate cancer diagnoses and targeted treatment, customer service chatbots and purchasing behaviour analysis.

What are the different types of AI and how can businesses take advantage?

The world of AI moves so fast, the possibilities of how it can help businesses are seemingly never-ending. To narrow it down, popular types of AI used most in high-performing apps, generally fit into these categories: 

Machine learning 

Algorithms working from huge datasets make it possible for computers to learn, make predictions or take actions. And they can do this without being specifically programmed to take these actions. 

You’ll find machine learning AI used for things like speech recognition, facial and image recognition, recommendation systems and predictive analytics. 

Large Language Models, LLMs

LLMs work within the larger field of natural language processing (NLP). They use algorithms and models to process, analyse and generate natural language speech or text. 

LLMs are used by voice assistants like Alexa and Siri, and translation apps like Microsoft Translate and Google Translator.

Generative AI

Unless you’ve been living under a rock, you’ll have heard a lot about ChatGPT. Powered by LLMs, it’s a tool developed by OpenAI which can understand and generate text, based on the prompts it receives. It uses language modelling and sequence prediction techniques to produce highly sophisticated written content and answer questions. 

Google’s Bard is another example of generative AI. Although it’s powered by a different language model and draws its information from the internet in real time. Whereas, as of May 2023, ChatGPT draws on a dataset limited to late 2021, but that’s a different conversation. 

You’ll find generative AI used in chatbots, and content generation. And lately, services such as our new AI Accelerator service.

How can we use AI in an app?

AI has taken the world by storm and it’s apparent that it can elevate any product that implements it. At the same time, the relatively low cost of implementation stacks up well against the benefits that AI can bring to your business. And it’s a technology that can be rolled out across a vast majority of platforms. 

There are countless proven use cases for AI across all sorts of sectors, including healthcare, banking, fintech, ecommerce, HR, hospitality, supply chain and marketing. 

If you’re bringing AI into a pre-existing app, integration can be through APIs or SDKs, which can leverage pre-trained models for the required tasks. These could include things like recommendation engines and voice recognition.

And if you’re building a new app, AI frameworks and libraries can be used in the development process. They can be tailored to your specific business needs for more control and customisation.
Woman in warehouse using mobile to manage her workload

Here are some examples of AI use by businesses

– Coca-Cola uses tools like ChatGPT and DALL-E for personalised advertising and increased operational efficiency. Coke also uses AI in purchasing and pre-ordering across Australia and New Zealand.

Their use of AI brings the soft drinks giant huge volumes of data, which they then use to generate further marketing decisions and unique and personalised experiences for their customers. 

– Amazon was a super-early adopter of AI tech. It has reorganised its entire structure to integrate AI into every part of the company, setting it up to become the largest e-commerce website in countless countries across the globe. 

Amazon’s algorithms have led the way in harnessing AI to boost the customer experience with personalised shopping recommendations. 

– Nike, the largest sports apparel company in the world has used AI to continue its growth trajectory. Using AI, Nike engages customers by launching customisable experiences.

Customers can design their own shoes both in-store and online. These experiences enable Nike to collect data, analyse it through their algorithms and use it to design future products. 

There are so many different ways AI can improve your apps and platforms. Here are a few examples of its potential in various industries:


From chatbots in personal finance apps to fraud detection, improvements in loan underwriting and risk reduction, the benefits of AI in the financial sector are fully appreciated by industry leaders. Potential cost savings for banks from AI apps are estimated to be around $447 billion this year.

Clinicians use AI algorithms in medical diagnoses, predicting outcomes and prognoses, and analysing data. This can speed up decision-making time and reduce the incidence of errors.

Supply Chain and Logistics 
AI can be used for improved warehouse management. That could include more accurate inventory management that would increase efficiency and speed delivery times.

E-commerce platforms can use AI-powered recommendation engines to suggest content to users based on their preferences and behaviour.  

Business woman with glasses looking on her mobile phone

But are there any challenges to AI?

Like everything, we must be aware of any challenges before entering your AI journey.

1. Data Confidentiality

Using AI has the potential to open you up to risks surrounding data collection and privacy.

2. Inaccuracy 

Preventing the potentially harmful consequences of inaccurate AI generated content and data should be top priority. Especially in highly regulated industries such as finance and healthcare. While there’s huge potential to harness the power of AI in these sectors too, it needs to be done properly.

3. Security 

Effectively navigating the challenging terrain of responsible and secure business applications of AI is a daunting task, as it holds the potential for significant harm.

However, we can provide assistance in navigating this landscape adeptly and safely. Contact hedgehog lab now and learn about our AI Accellerator service.

Artificial Intelligence & Machine LearningClient servicesGrowthTech

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