Historically, AI tools have been the domain of the tech-savvy.
But with the release of tools such as ChatGPT-3 and Google Bard - tools which anybody with any level of technological knowledge can use and benefit from - we have seen a huge increase in conversations surrounding Gen AI.
This shift offers a real opportunity to businesses: to embrace new tech and supercharge the capacity and capabilities of their people.
While this sounds great in theory, it is particularly daunting in practice. It requires digital, innovation and marketing leaders to think carefully about how Gen AI would benefit their business, as well as what guardrails and policies they would need to put in place for optimal outcomes and minimum risk.
Most enterprises we talk to don’t know where to begin. And we don’t blame them. We asked three of our top specialist digital & innovation agency leaders for their views on the topic, to help guide your Gen AI journey.
StudioSpace agency rehab_agency is phenomenal at creating unfair advantages.
As a digital innovation team, they strive to deliver growth for consumer-facing brands through culturally relevant creative and tech. Callum Gill, their Head of Strategy, shared his insights with us.
Another GenAI pioneer, who co-founded the first GenAI training agency in the UK, is Barry T Whyte. His agency, Electric Sheep, promises to make AI work for your business in just three hours.
We also really valued the insights Ed Marshall, CTO at hedgehog lab, an agency which, amongst other things recently partnered on a campaign with Under Armour, which used AI to write ‘The Ultimate Team Talk’.
They tested the limits of ChatGPT’s human-like capacity to create a motivational script specifically coordinated to “utilise language that invokes a fierce sense of camaraderie and a defender mentality”.
They’ve provided practical guidance to empower you on leveraging the potential of Gen AI to positively transform your business.
Part human/Part Machine
Right off the bat, our experts agree: GenAI is a friend, not a foe.
“In a world driven by growth metrics such as GDP, using GenAI merely to maintain productivity doesn’t seem logical. Instead, GenAI should be utilised to enhance team output, rather than merely for cost-cutting measures,” says Callum of Rehab Agency.
“Often, there’s a misconception that AI is replacing humans, but it’s more accurate to see it as augmenting human capabilities, making them better by even 10% or 40%. This perspective offers a healthier conversation than the misconception of machines taking over jobs, a narrative that has been present since the Industrial Revolution.” adds Barry, co-founder of Electric Sheep AI Training.
A great example of this is GitHub Copilot, which has a transformative effect on software development, boosting efficiency by up to 80%. This efficiency wave, initiated by Copilot, is set to wash over other sectors, including marketing and sales.
The knowing-to-doing gap & the need to identify use cases
When it comes to GenAI there’s definitely a knowing-doing gap.
Enterprises know that GenAI is something they should be looking into, but they don’t really know what to do about it. As a result, there’s a gap between experimenting with these tools and their ethical, safe, and successful deployment.
It’s likely that the largest “barrier” when it comes to adopting GenAI in a business environment is the fact that enterprises don’t yet know how best to approach and apply it to drive strategic organisational outcomes.
While every organisation will have unique objectives, example use cases can include:
GenAI has the power to gather and analyse large quantities of data and generate insights quickly, reducing the amount of time spent on this work from weeks to hours. These insights, in turn, can aid in the rapid ideation process, helping to discard bad ideas quickly or iterate around a theme to focus on potential strategies.
GenAI can significantly speed up the campaign validation process, which is often a long, costly, and time-consuming endeavour. Businesses can, for example, draw on GenAI to help simulate and experiment with audiences built on real human data for more accurate validation, offering a substantial benefit to clients.
“We’ve recently worked with a financial investment firm which, instead of using AI like GPT for direct interactions, is leveraging it to provide insights on portfolios through their app. In doing so, this financial investment firm uses GenAI to underpin its product itself, helping the product deliver some of its functionality through a GenAI plugin,” says Ed of StudioSpace agency hedgehog lab.
Another project that’s particularly creative - demonstrating the range and diversity of GenAI use cases - is the project hedgehog lab lead for Under Armour.
“We worked closely with Under Armour’s marketing team and used GenAI to create the world’s most motivational speech,” Ed added.
If there was one concern that our panelists had, it was about AI’s potential to replace those working in the customer service sector.
“There are also plenty of use cases in customer service, so if there is any industry where I would be concerned that GenAI may replace humans and massively repetitive manual work, it would be in customer service,” Ed explains.
GenAI Challenges: Beyond the Technical
Teams often face challenges in accessing data vital for AI-driven projects. As the project progresses, opinions might shift regarding data accessibility, causing projects to restart and resulting in development challenges.
An identified phenomenon, termed “good bot syndrome,” describes GenAI’s tendency to provide answers even when it might not understand the request fully. This can result in the tool presenting incoherent or unrelated ideas in its bid to offer a solution. Efforts are underway to engineer controls, enabling GenAI to admit when it lacks enough information or is unsure of its response.
Another significant challenge is the public’s perception of AI, which varies by industry. While some sectors are receptive, others, like the gaming industry, resist GenAI’s involvement in creating game elements.
Misinformation about GenAI’s capabilities, often fueled by the media, creates skepticism, leading platforms to ban AI-generated content. This means that audience engagement, both internal and external, becomes even more important; no matter how advanced the AI tool, its effectiveness is void if the audience is not on board.
A general lack of knowledge about AI’s data security methods certainly contributes to some of this misinformation. Rehab Agency’s Callum reassures us that “on its surface, the problem with data security stems 9 times out of 10 from human error, rather than digital. AI is effectively a black box to a certain extent.”
He reminds us still that it is important to make sure we’re using the correct APIs to avoid data breaches amongst consumers.
Barry from Electric Sheep also had a few words to say about misinformation regarding AI: “addressing misconceptions and educating people about GenAI’s actual capabilities is essential to overcome fear and also to ensure that they are actually equipped to maximise the value that the tool that is GenAI can offer them as support.”
Of course, there are also regulatory challenges that need to be taken into account. Regulation shouldn’t be seen as an impediment, especially when tech giants like Google and Microsoft have deeply integrated GenAI and addressed security concerns. The real challenge lies in moving from trial phases with GenAI to actual production in a secure manner.
But just how exactly should your organisation facilitate this move?
Our experts suggest a few methods.
- Prioritise immediate, small-scale changes.
- Define your AI use case early.
- Understand that AI technologies are fluid.
- Garner top-down and bottom-up support.
- Be proactive in AI adoption.
- Think creatively about AI applications.
In conclusion, GenAI signifies a pivotal shift in the business landscape, democratizing AI accessibility. It empowers businesses to augment human capabilities, not replace them. Examples like GitHub Copilot showcase significant efficiency gains.
However, the “knowing-doing gap” persists, hindering effective GenAI integration. To bridge this, businesses can explore use cases like rapid insights generation and streamlined campaign validation.
Beyond technical challenges, non-technical obstacles such as data accessibility, the “good bot syndrome,” public perceptions, and regulations also loom. Overcoming these hurdles requires adaptability and strategic planning.
In essence, GenAI offers businesses an unprecedented opportunity for innovation and efficiency. By viewing it as an ally and not a threat, organisations can thrive in an AI-driven future, shaping its role in their operations. Challenges are surmountable with the right approach, positioning businesses at the forefront of AI’s transformative potential.
If you’re looking for access to the replay of StudioLive (the event where these insights were originally shared), then you’re in luck. It’s available for a limited time, so be quick!
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