In the technology sector, whether you’re a tech startup or an established player, staying relevant today requires actively engaging with the conversations that are happening around current AI trends. But rather than blatantly jumping on the AI bandwagon, your PR and marketing content should aim to address how these issues impact your brand or your customers and highlight the unique insights and expertise your company brings to the table.
So, here are five key AI topics that should be on your radar for a compelling tech PR content strategy.
1. How are we going to cut the carbon footprint of GenAI?
The huge (and growing) carbon footprint of AI – and generative AI (Gen AI) in particular – is becoming a major concern and is sure to be a media hot topic over the next few years.
There’s been so much excitement about the power of Gen AI to automate and streamline business processes. But one major downside is that training Large Language Models (LLMs) and processing Gen AI requests is very computationally (and energy) intensive. This means Generative AI consumes huge amounts of electricity in data centers that mainly burn fossil fuels. And the problem is escalating.
Research by Morgan Stanley suggests that by 2027, generative AI could use as much energy as Spain used in 2022. And now, the general public is becoming aware of the significant environmental impact of AI.
A UK survey suggests that 54% of people who are familiar with Gen AI now know that its expansion is likely to damage the planet. 45% want laws forcing AI companies to be transparent about their environmental costs. One out of five don’t trust companies like Open AI to act responsibly in managing and reducing their environmental impact.
2. The rise of Agentic AI
Agentic AI is one of Gartner’s top strategic technology trends for 2025. The IT industry analyst defines Agentic AI as systems that “autonomously plan and take actions to meet user-defined goals”. Another definition is: “an intelligent software system designed to perceive its environment, reason about it, make decisions, and take actions to achieve specific objectives autonomously”.
Rather than simply responding to user prompts, AI agents have the ability to make plans and take action (involving multiple steps) and check that what they are doing is actually working to achieve an overall goal. For example, in financial services, an AI agent might be able to detect unusual activity in a customer account, trigger a temporary freeze, and notify the customer, telling them about the next steps.
Gartner predicts that by 2028, at least 15% of day-to-day work decisions will be made autonomously through agentic AI. And over the next few we can expect AI agents to be a major part of the AI conversation.
3. AI ethics and regulation
How do we regulate AI and ensure it is used ethically and responsibly? There are many sides to this, from ensuring that data used in LLM training does not infringe copyright or personal privacy, to eliminating bias, discrimination and the spread of misinformation through AI applications. There are also worries about deepfakes and AI being used in scams. At the extreme, some experts fear that if AI is left unchecked, it could pose an existential threat to mankind.
We need regulations and guidelines about how AI systems are built, deployed and used. The EU AI Act became one of the earliest legal frameworks to try to regulate AI, and it’s likely to be a blueprint – or at least a starting point – for similar AI laws in other parts of the world. It’s important, however, that regulators strike a balance,
While protecting against the dangers of AI is important, the regulations must not stifle innovation or stop us from reaping the positive benefits that AI can deliver.
There are many perspectives on this subject, so it will be a media and PR hot topic for many years to come.
4. Open-Source AI versus Closed AI
The essence of the open-source AI debate revolves around whether AI companies should openly share all the details about how they build their AI models – or keep this information to themselves so they can maximize their commercial potential.
The open-source AI philosophy advocates for AI companies to provide free access to the training datasets, weights, and other processes used to build their AI models – to anyone who is interested. In this way, the ‘open-sourcers’ argue that it’s possible to tap into a diverse global community of developers and experts who can contribute and collaborate on building AI. This paves the way for faster development cycles and has the potential to trigger innovations that might not otherwise emerge.
Those who promote a closed approach to AI suggest that keeping more of the essential inner workings of the AI models in-house within the company that built them ensures more secure systems. It also incentivises investment in rapid innovation (by allowing companies to maintain a competitive advantage that lets them more easily monetise their efforts).
5. Artificial General Intelligence
Artificial General Intelligence (AGI) is typically defined as AI that reaches a level of intelligence equal to or exceeding human-level intelligence (in its ability to reason, learn, make decisions, etc.). Although AI has taken some huge strides in recent years, most experts agree we are still far from achieving true AGI.
However, that doesn’t stop big AI companies and experts from constantly referencing AGI as an overall goal. They are endlessly speculating on how close each new breakthrough or innovation is taking them on the path to achieving AGI.
AGI is AI’s holy grail, so you can bet it will be a trending media topic for a long time.
Finding relevant and considered ways to incorporate these trending AI themes into your PR and content marketing can help you stand out and be noticed.
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