Beyond the hype: Navigating the future of generative AI

Following a year where artificial intelligence (AI) has sprung onto our radars in a way never seen before, we're now entering a time when AI moves on from being a novel pursuit and gets fully integrated into the business.

As a marketing leader, I've seen many specific use cases for AI that have proved useful. For example, generative AI tools have helped teams with the creative and ideation processes that are central in many marketing campaigns and helped to drastically reduce time spent researching and planning.

For example, we might have a customer newsletter that needs enhancing with news and updates relevant to their industries. Or we might need to quickly tailor some copy for different audiences that mirrors the same messaging structure. For anyone that's used tools such as ChatGPT in the past year, these use cases alone may not sound groundbreaking, but they have brought fresh perspectives to our teams and freed up hours of time which can be spent on more meaningful tasks. 

What we're likely to see from AI in the near future is more pragmatism and action that will help businesses make decisions at the highest levels. Let's take marketing again as an example. Most teams will have access to tools that will measure the success of a campaign. They'll know how many views a campaign received, the quantity and sentiment of press coverage, and the countries that connected the most with the marketing message. 

The stats themselves can be useful, but marketers will know that explaining why a campaign performed the way it did can be a challenge. For example, why did certain regions fare better or worse than others? The data will arm you with the facts, but what more businesses need is the insights that help them create the story behind the numbers and suggest improvements. 

This is where generative AI will help companies go from insights to actions – which should be the goal for all areas of a business, not just the marketing team. Now that technology is advancing at an exponential rate, we'll see AI creating value that builds on existing work and contributes to a more profitable organisation through fact-based decisions. 

It's important to note that this change might require leaders to adapt the culture of teams to reflect this new era of decision-making. As part of this effort, leaders should proactively communicate their vision for generative AI within the business and seek to deliver a roadmap to success, taking every team on this journey with them.  

Fairness and safety first

As with any transformational technology, it's important to remain cognisant of and openly discuss the risks involved. For example, there are some legitimate fears that the tool will replace humans in the workforce. 

To help ease any anxieties, AI should always be viewed and communicated as a way to enhance what humans can already do. Generative AI can perform well in many scenarios, but human oversight continues to be needed to spot mistakes or biases, for example. I don't believe that jobs will immediately be taken over by AI but rather that they will be shaped by AI. It will likely be the case that organisations that are proactive in innovating with AI tools and training their staff to use them to become more productive and decisive will be the most successful. 

As we train our staff on the best uses of AI, it will become increasingly important to also train the AI models themselves to be fair and ethical. If we're going to increase our use of AI across sectors, there's a danger that biased algorithms could contribute to a biased society that favours those who are already favoured. If organisations fail to do so, the odds could be stacked against our marginalised communities even more than they already are. 

It's going to be a difficult battle to completely remove bias in AI systems for many reasons, including a lack of diversity in data sets or the inherent and unconscious biases of those developing the systems. However, it's going to be a major societal issue that we will all have to address together. With the US executive order for AI and artificial intelligence act in the EU, it's inevitable that the fairness and safety of AI systems will be a significant talking point for years to come.   

Understanding the risks

I'm excited about how companies will use AI in different ways as the capabilities of the technology become more diverse. However, there are elements of risk that should cause organisations to proceed with caution. That's why we should expect to see greater focus on generative AI safety and best practices over the coming years and why I'd encourage all leaders to consider what these efforts should involve at their organisation. 

The change taking place before our eyes is the transition of AI from novelty to business essential, with generative AI tools already proving valuable – in marketing and beyond. The focus will shift towards actionable insights, moving beyond data to understand the 'why' behind marketing campaign results or other business reports. Ethical and data security considerations will be paramount, requiring a collective effort to ensure fairness, equity and safety in AI applications. Striking a balance between innovation, ethics, and privacy will define the transformative journey of AI.