Machine Learning Models and Large Language Models are the hot topic of discussion on almost every marketing podcast and strategists’ agendas at the moment. Leaders, marketers, business owners and heads of operations are all looking at the implications and uses of this technology with mixed feelings. Many may feel that they are being left behind or don’t know where to start with adoption, as this technology has developed so rapidly, especially in the 2023 to 2025 Q30 period.
On the one hand, MLMs are nothing new in terms of Paid Media technology, having been used across major advertising platforms such as Google and Meta for over a decade. LLMs are a newer concept and have become very popular in the mainstream, but there are many equally valid and exaggerated concerns about the implications of the technology.
We cut through the noise in this article and go through the impact and implications of MLMs and LLMs in paid marketing and the wider business landscape. Are these technologies going to change the world at a rapid pace, and how do businesses need to leverage and take advantage of these technologies whilst also maintaining ethical and legal responsibilities? We answer all of these questions and provide future predicted trends as to where these technologies are likely to go and where they will likely be best implemented into business workflows and paid marketing.
MLMs – Are Going Far Beyond Forecasting, Targeting and Campaign Optimisation
MLMs have gone far beyond forecasting and targeting, as well as campaign optimisation. They are now fully integrated into most, if not all, major tools. They have been a core feature of Google Ads’ systems since 2014, and this has extended to other tools and programmes using machine learning in almost all operations. With large data sets, MLMs are the best in terms of analysis and making informed optimisations, with this technology exploding in popularity and implementation alongside agentic Large Language Models.
Machine Learning’s Previous & Current Role in Paid Advertising
Machine learning was incorporated into Google Ads in 2015 to improve bidding and ad targeting, so it’s not a new concept within paid advertising when compared to newer technologies. With 2016 seeing the implementation of Smart Bidding, bid automation was the core objective of ML capabilities. Fast forward to today, and it’s a core aspect of precision targeting, dynamic pricing, personalised ad experience, ad optimisation and other specialist applications such as predictive analytics and advanced fraud and policy violation detection.
What Have We Seen Being Introduced Recently?
Alongside these use cases and technologies from Google, Performance Max Campaigns also utilise Google AI and ML for these optimisation purposes. Meta also utilises ML for the same core features, and the main aspects that we have seen introduced recently are rapid advancements in the systems to continually improve targeting, bidding, and performance. These algorithms and models progress by the day in terms of their exposure to data sets and the ways in which they are optimised to enhance campaign performance. This is why it’s important to look into the future to see where machine learning can take paid advertising to new heights.
What to Expect From Machine Learning in the Future
Ethical practices being combined with providing additional value for potential clients/audiences is one of the core challenges of the new world where advanced machine learning and large language model systems will be integral in a wide range of functions. As of writing, they are already becoming a core part of swathes of industries, and machine learning will likely continue to have a huge impact on paid advertising and performance marketing.
A Greater Emphasis on Technological Approaches – Technological advancements are not new, and they will continue to influence campaign strategy and tools going forward. A proactive approach is required to embrace these technologies and tools and not be left behind.
Ethical Responsibilities – Marketers will have to continue to keep ethical considerations in mind. Fairness, transparency and accountability are core features of ethics when using machine learning models. Marketers also have the responsibility of checking data and insights for AI hallucination and other fact-checking exercises to ensure that the data is accurate and a fair representation when making assumptions based on the data.
Continuing to Provide Value to Audiences – As targeting gets even more advanced, it’s important to provide the best value and experience to the user. This is regulated with Ad quality score and other metrics, but it’s very important that marketers continue to provide the best value and relevancy to audiences despite automation being readily available. These tools free up professionals to provide the best experience possible to the user.
Embracing Advanced Machine Learning With Enhanced Campaign Modelling and Forecasting
As tools continue to advance, this enhances and frees up time for campaign management and forecasting, as discussed. Embracing these technologies and being ahead of the curve is vital to ensuring that you are using all of the available technologies to maximise campaign performance and use the full power of advanced modelling and forecasting.
This is where our performance marketing consultants can help. We regularly stay up-to-date on the latest tools that are available, as well as how these can be used to enhance campaign performance and support forecasting and campaign management.
Conclusion
Machine learning is nothing new in paid advertising and has been heavily used in Google processes since 2015. These technologies continue to grow, and the amount of data that these systems leverage and analyse means that they continue to develop in complexity. This is a tool that will continue to be leveraged going forward. It’s highly important to get ahead of the curve with the application of these tools and implement them into your processes. There are ethical responsibilities that will need to be observed and perpetuated by experts in the industry as these tools become more prevalent in mainstream digital paid advertising.
LLMs – The Future of Business Operations as We Know It
Large language models and agents have been catapulted into the spotlight and have seen widespread adoption by all current generations. This is an adoption of new technology that has been unprecedented, far exceeding percentages in early adoption of mobile, PC and even the internet itself in its initial inception. Everyone in paid and performance marketing is using some form of AI agent or tool to enhance their day-to-day jobs and campaign performance. Going beyond this, many businesses are adopting their own agents to transform their workflow. It’s been argued as one of the most impactful pieces of technology that humanity has ever seen, especially with future projections. But how powerful are these tools, and how do they need to be harnessed ethically?
LLMs and LLM Harnessing Agents Have Gone Far Beyond ‘Basic Tools’
Agents have far surpassed basic tools; they have completely transformed workflows as well as the way that users search online. Google has adapted and developed AI oversights that seek to compete with mainstream LLM agents, and it’s quickly become an arms race between major Search conglomerates and their development teams to gain an advantage or be quick to market as competitors in the AI search and agent space. These tools have now far surpassed their expectations, and from the evidence that we see, they’ve been largely adopted into everyday life. This goes further to all kinds of business applications, especially within performance marketing.
Agentic Solutions Have/Are Completely Transforming Business Workflows
Automated workflows and automatic replies to emails, all the way to advanced processes such as finance applications and insurance filings being reduced to mere minutes from hours, business workflows have been completely transformed by agentic solutions. As these technologies become commonplace in all workflows, it’s important to leverage them to their highest potential, but also to ensure that they are used correctly and that outputs have human reviews before any workflow solutions are implemented.
How Agentic LLMs Will Influence the Paid Marketing Stratosphere
There’s no doubt that agentic LLMs have changed all technology-based businesses. When we specifically look at the paid and performance marketing industry, LLMs and paid advertising go hand-in-hand; they complement each other extremely well. The likely outcomes will be that automatic and dynamic ad assessment and ad creation are a very real possibility. However, with automation and truly relying on these tools, ethical considerations and concerns do arise.
Should We Be Concerned About This Growing Technology? – Ethical Considerations
This technology has exploded in popularity and adoption, especially in mainstream use. AI hallucination is the most prevalent aspect that affects the ethics of large language models and LLM agents.
AI hallucination is the phenomenon where LLMs or other systems generate random, incorrect, nonsensical or incorrect information. Even when presented with accurate prompting and datasets.
Marketers need to continue to vet the outputs of any LLM or AI workflow to ensure that the information that is generated or the specific ad text output is accurate and best serves users. This is the human element that AI will be extremely unlikely to ever replicate or replace.
How Marketing Strategists Will Grow, But Will Still Continue to Be a Key Piece of the Puzzle
These LLM agents are still going to be utilised as a key tool, and it’s unlikely that they will ever be able to replace human experience, as well as pragmatic and sensible approaches to the responses and data that are produced. It will still be highly important that this human element exists and that outputs are regularly monitored for accuracy and for ethical requirements. This will continue to be a core element of the use of LLMs and Agentic LLMs to enhance paid marketing workflows as well as campaign performance. So marketers will continue to be a core part of the process, but will need to learn how to leverage these tools to enhance the experience for potential audiences as well as further enhance their campaigns and workflow efficiency.
What Are the Future Predicted Trends and How Much Impact Are We Going to See?
Many feel that LLMs will become a part of everyday life. With the rapid adoption of major tools such as Chat GPT, Claude, Google Gemini and other assistants, it’s become a very mainstream technology. We have also seen non-Google search engines take a notable chunk out of Google search, which has always been a global search powerhouse, controlling over 90% of global searches each year. It’s likely that these technologies are going to continue to get more advanced, and the future will be interesting to see if safeguards and legislation is put into place and just how widespread agentic LLM adoption will be for all businesses.
Conclusion
AI is a huge topic, and LLMs are becoming more and more prevalent in everyday life. Businesses face the risk of being left behind if they do not adopt these technologies into their workflows and the potential for LLMs to enhance all aspects of the world is looking limitless. This, however, comes with ethical risks, and this will be the fine balance that marketers will need to strike as this technology becomes more advanced by the day.