AI is becoming an indispensable tool for supporting the evolution and effectiveness of brand building. 

Undoubtedly it can provide the flexibility and data-driven insights necessary to allow brands to adapt and thrive, particularly to increase personalisation and content relevance.  AI’s capacity to analyse vast amounts of consumer data to identify emerging trends and preferences, can help brands adapt their hero assets to remain relevant and appealing. 

But while AI offers insights and data for planning, it falls short on creating truly distinctive brand assets, logos for example. The craft and insight gained from years of individual and collective experience, empathy and understanding remain a more powerful tool for creation.

Let’s explore what’s good about AI, what’s bad and what’s the reality when considering how to use it to build long-term brand fame and affinity. 

## The Good
AI assistance can help speed up several stages in the brand building process:

### AI and Colour 
AI can assist in colour selection by analysing a colour’s psychological and cultural associations. This data-driven approach can help brands choose colours that not only align with their values but also evoke specific emotions in consumers. 

But when AI algorithms monitor colour, it’s worth remembering that they’re just watching trends. So, while we may think it’s a good idea to make adjustments to keep a brand's colour palette fresh and appealing, it makes for a here-and-now-approach, not one that builds longevity. 

### AI and Logos  
AI can aid in logo design by analysing vast datasets of successful logos to identify patterns and elements that, at a moment in time, resonate with audiences. This data-driven approach can support with creating sets of potential logos as a starting point.

Some may say that AI-powered tools will allow you to continually assess consumer sentiment towards logos, helping brands to adapt and refine their visual identity based on real-time feedback. But is that ability to adapt to changing consumer preferences also able to ensure the logo remains a powerful representation of trust and reliability? We would say not. 

### AI and the words: Brand lines and TOV  
AI is able to assist in creating memorable lines, by analysing linguistic data and consumer sentiments. Natural Language Processing (NLP) algorithms can help brands understand what words and phrases resonate with their target audience. These insights can then guide the creation of straplines that not only encapsulate the brand's essence, but also align with the current cultural conversation. But the nuances and empathy that a writer, strategist and brand marketeer bring is still needed to ensure the lines truly do hit home.

Additionally, AI-powered chatbots and virtual assistants are now becoming extensions of a brand's voice, helping to reinforce straplines and brand identities in customer interactions. Programming chatbots to assume a brand’s tone of voice can prevent customers feeling alienated in automated spaces. However, there is a bigger question at play: if authenticity is key to a brand, does the mere presence of an AI chatbot negate that brand experience? 

## The Bad
However sophisticated the AI, it still has various drawbacks:

### Lack of Creativity
AI is based on algorithms and patterns, which limit its ability to generate truly innovative and creative ideas. AI-generated designs that follow popular trends and templates are likely to result in brand assets that look generic and fail to stand out. Building a brand requires out-of-the-box thinking and emotional resonance, which remain challenging for AI to replicate.

### Loss of Human Touch
The most successful brands are built on creating genuine emotional connections with users.

AI lacks the human touch and emotional understanding that are crucial when crafting brand assets that resonate with the target audience.

### Inconsistent Brand Messaging
While AI can help automate certain aspects of brand communication, it may not always understand the nuances of a brand's values, mission, and voice. This can lead to inconsistencies in messaging, which can be detrimental to brand identity.

### Ethical Concerns
We strongly believe in using AI responsibly. This includes being aware that AI algorithms are only as good as the data they’re trained on. Biases present in the training data can lead to unintentional biases in brand assets, which can have negative social and ethical implications.

### Limited Understanding of Cultural Nuances
Branding often involves understanding and respecting cultural nuances. AI may not have the cultural sensitivity required to navigate diverse markets effectively, potentially leading to cultural misunderstandings or insensitivity. This is particularly true when creating global brands that are also locally relevant.

### Energy Guzzling
While undoubtedly a powerful tool to help explore brand building, using AI comes at a considerable energy cost. It relies heavily on the computational power of servers and vast server farms, often powered by energy-hungry data centres. These are packed with high-performance hardware and require an immense amount of electricity to function efficiently.

As we explore the exciting possibilities of AI in brand and content creation, it’s crucial to recognise the environmental impact of these energy demands. Balancing innovation with sustainability is paramount in harnessing AI’s potential, while minimising its environmental footprint.

## The Reality
While AI can be a valuable tool in the branding process, we believe that it must be used judiciously and in conjunction with human creativity and expertise. The downfalls of AI in branding for the long term largely revolve around its limitations in creativity, emotional understanding, and cultural sensitivity.

Successful branding efforts involve a harmonious blend of AI-driven data insights and human-driven creativity and intuition, to create brand assets that truly resonate with the target audience and reflect the brand's unique identity.

Our view is that AI is a useful tool to speed up exploration. But it’s not an answer in itself. It’s great for finding averages and trends. But not for standing out or disrupting sectors.
It can only remix the here and now.

__Here’s our best practice advice for brands thinking of using AI tools and approaches: __

1. __Balancing Human and AI:__ Use AI as a tool to enhance human creativity and decision-making rather than replace it. Combine the strengths of AI (data analysis, automation) with human insights (creativity, intuition).
2. __Ethical AI Usage:__ Be aware of potential biases in AI algorithms and take steps to mitigate them. Ensure ethical AI practices to avoid unintended consequences.
3. __Continuous Learning:__ Invest in ongoing training and education to stay updated with the latest AI tools and techniques relevant to brand management.
4. __Testing and Validation:__ Before implementing AI-driven changes to brand assets, conduct thorough testing and validation to ensure they align with the brand's core values and resonate with the target audience.
5. __Human Oversight:__ Maintain human oversight in the branding process. Human expertise is crucial for assessing the emotional impact of brand assets.
6. __Flexibility:__ While AI can provide valuable insights, be willing to adapt and make changes based on qualitative feedback and evolving market dynamics.

If you’d like to discuss how to assess your brand’s ability to thrive in an AI driven world of urgency, please contact us at [hello@teamspirit.co.uk](mailto:hello@teamspirit.co.uk).

AI is becoming an indispensable tool for supporting the evolution and effectiveness of brand building. But while AI offers insights and data for planning, it falls short on creating truly distinctive brand assets. Find out more in our latest article. 

At the end of last year, the rumblings around a new chatbot appeared on the internet and then quickly went viral. Launched by Open AI, ChatGPT (short for Chat Generative Pre-Trained Transformer) racked up one million users in five days (for context it took Twitter nearly two years to hit the 1m mark). 

The system is trained on an incomprehensively vast dataset of websites, articles and books – an estimated 175 billion data points – and had users flocking to the site to engage with the potentially revolutionary chatbot and ask it questions such as “How Do I Cook Lasagne”.  

However, it was quickly realised that its capabilities were far more sophisticated, and that it could be used to write code, build websites, work as a customer service bot and as a virtual assistant. It can also write essays, copy, and press releases if given a brief.  

It was at this point that the questions were posed: is there a malevolent undercurrent to ChatGPT – is it going to steal our jobs, bring the education system to its knees and ultimately usher in a new dawn of communication, creativity, and life as we know it?

Probably not, no. 

The main concern for brands, as well as PR and Marcomms professionals and digital media in general, is the fact that ChatGPT is a remarkably efficient search engine (though it’s very important to caveat that its current knowledge ends in 2021; it lives in a world where the Queen is still alive, and Liz Truss was never Prime Minister). 

While Googling something will take you to a page of websites and links, ChatGPT will give a detailed and insightful answer, with no commercial interests or bias. You can’t leverage your brand appearing higher up than a competitor, something which is bad news to the marketing and PR specialists who have spent many years carefully curating their online shop windows with content, adverts, and media coverage to give themselves a digital edge. 

Google recently issued a “Code Red” in response to the launch of ChatGPT and the threat it may pose to their online advertising revenue, triggering what could be an AI “Arms Race”. Google have announced today that they are launching their own rival, called Bard. 

In terms of the day-to-day, many are reporting that they are already utilising ChatGPT in their working lives, generally for simple data analysis and helping write copy, from emails to reports. 

However, it is difficult to get anything but a first draft out of the technology. ChatGPT is drawing on data and algorithms fed to it to mimic human responses, but with any mimic, there is a sense of the uncanny about it. 

While eloquent, there is a robotic-quality to the copy generated, a clipped over-professionalism, leaving the reader inevitably feeling unsettled if they assumed it had been written by a real human – even if they can’t put their finger on why. 

You also can’t build professional and personal relationships with AI, no matter how much they may be able to sound like us, and they are of course not able to offer an original, or creative, thought or idea. 

For those who are saying that ChatGPT marks the future, there are just as many saying that it will be relegated to the pile of things that could have changed the face of the world but just didn’t take off, that currently includes Google Glass and the Segway. 

What will be interesting to keep an eye on is how ChatGPT will inevitably need a revenue stream to sustain itself with so many users. A subscription model which promises faster response times and access to new features is being piloted, but at the low price of $20 per month, this won’t generate much income for its founders OpenAI. Until then, we must assume that the adage of “if the service is free to the user, then the user is the product” applies, though it remains to be seen to what end. 


Is ChatGPT the future, or is it destined for the pile of things that ‘could have’ changed the world. Antonia Phillips, Associate Director and Digital PR Guru, shares her view on whether we should all be worried.

*In the second part of our trend mini-series, we take a look a what the growing desire for instant gratification means for financial services.*

Now, in the third age of computing, the cloud is allowing processes to take place seamlessly, with users now free to interact with data and information as desired. We know that everything is searchable, streamable and accessible. 

Moreover, we expect to get information instantaneously or at the very least receive real-time updates. And when that happens, we tend to trust that service far more.This ‘now’ mentality is a driving a new commercial model, with monthly subscriptions being replaced with real-time access, eg a movie stream or a live football match.

And we’re happy to pay there and then through micro-payments. This appetite for the instant has already had a profound impact on the financial services industry. 

Payment has become seamless and instant, with services such as PayM allowing users to be identified and pay their contacts through their mobile phone number. And Trussle, powered by AI, is transforming mortgages by making previously onerous user tasks invisible and providing straight-through access to broking. 

As a key user expectation, expect to see instant, frictionless flow continue to pervade other financial services.

Implications for Financial Service brands:
<br><br>
  -  Users want the world to flow. They expect services to be frictionless and invisible. Brands will need to be clear about the value they add.
  -  Users will shape the reality they want. They will run their lives with multiple small flows of information and data that allow them to be most efficient – and to change their decisions instantly.
  -  Companies that are not able to provide their customers with information in real-time will start to become less trusted and will ultimately lose market share.
<br><br>


*This blog is taken from our [whitepaper on trends](https://www.teamspirit.uk.com/what-we-think/white-paper/2018-and-beyond) in financial services, marketing, PR and tech, ‘__2018 and beyond__’.*

Developments in machine learning, a type of artificial intelligence (AI) technology, could soon mean that [computer-generated forgeries](https://www.economist.com/blogs/economist-explains/2017/07/economist-explains-3?fsrc=scn/tw/te/bl/ed/howfakenewscouldgetevenworse) of original content are appearing more frequently in your feeds. 

The manipulation of imagery and videos is nothing new - humans have been adapting these media from the outset for the sake of art, satire and also fraud. 

What makes the introduction of this new generative adversarial network (GAN) technology into the mix so significant is that it requires no trained skill - and most importantly since the content is generated by a computer, other computers will regard it as real. 

Unlike fake copies created by humans, which may include an incorrect pixel or two, this method of automatic content creation is required to have fooled a piece of verification software in order to have been generated in the first instance. 

At the moment this method of content generation is only possible at low resolution, but as the software becomes more powerful it could well be that we are soon witnessing fake content which is harder and harder to decipher from the real thing. 

Developments in machine learning could soon mean that computer-generated forgeries of original content are appearing more frequently in your feeds. 

Counterfeit content round the corner

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