It’s a new year, which means that it’s time to map out a pathway forward, and put some kind of plan in place for your business or personal brand growth (if that’s what you’re after) in 2026.
But with so much changing so constantly, it can be hard to know what you should be focused on, and what skills you’ll need to maximize your opportunities. With this in mind, we’ve put together an overview of three key elements of focus for the new year.
Those key elements are:
- AI
- Algorithms
- Augmented Reality
These are the three elements that are going to have the biggest impact on social media and digital marketing in 2026, and if you can get them right, you’ll be best placed to get the most out of your efforts.
So, this first post in the series will look at AI, which has become the major tech trend of the moment, and may still have a transformative effect on various aspects of your process.
The AI dilemma
Yes, this is a dilemma, because while many people are loudly yelling that AI is the future, and that you must use AI or be left behind, keep in mind that those people yelling the loudest are the ones who stand to benefit the most from broader AI adoption.
As with all new technologies, grifters will latch onto the latest trend, then use the knowledge gap of said development to prey on businesses, who know that they need to understand what this latest thing is all about, but don’t have the capacity to tap into it by themselves.
The problem is, most of these grifters don’t know much more than you do, especially in this latest AI push. That’s because AI is, by design, built to work in an assistive capacity, so it’s there to help you learn, grow and develop, through basic conversational prompts. You don’t need some self-proclaimed “AI expert” to tell you how to use it, you just need to know what you want to use it for, and then, the right questions to ask to get the most out of it.
Which is the real trick. Much of the AI hype revolves around AI replacing humans, and taking over roles through advanced automation, in a range of ways. But AI tools are not designed to be wholly replacive, they’re complementary, they make people who already know what they’re trying to do better by providing alternative angles and suggestions, which, if you know what you need, could be helpful. Or they could be crap. If you don’t know the difference, then an AI tool is not the solution, but a shortcut to, in most cases, poor quality results.
The risk of relying too much on AI is that it makes you and your business look cheap, like a brand that will cut corners to save a buck, “and if they’ll cut corners on the design of their logo, what else will they take liberties with?” AI results are pretty good, they’re estimations, based on what already exists. But they’re not great, they’re not perfect, and over-reliance on AI will sink you (as several businesses have already found).
Striking a balance in AI use is key, and as such, it’s important to understand both the capacity and the limits of AI in varying capacity:
- AI is great for generating images, but not great for originality. If you’re an artist who knows how to edit and shape images, how to understand graphical depictions and visual storytelling, if you understand the visual you’re trying to create, then AI tools can streamline creation. But they shouldn’t be the sole solution. Everyone can tell it’s AI-generated. Everyone.
- AI is great for ad targeting, with Meta’s systems getting increasingly good at finding the right audience for your ads, even if you wouldn’t have targeted them manually. In fact, this is worth a point of clarity: The current wave of tools that we’re referring to as “AI” are not actually artificial intelligence at all, they’re machine learning systems that have been taught to understand an expanded range of inputs, and produce a result in line with what’s requested. There’s no “intelligence” here, these systems have no understanding of the outputs they produce, they’re just analyzing the input data, and outputting a response. These systems are not “thinking” any more than a calculator is thinking as it provides a response, this is machine learning, and Meta has been leading the way on machine learning for years (with its ad systems and feed algorithm in particular). These new systems are much better at data matching, because they can do so on a much, much larger scale, due to massive increases in data processing capacity. But they’re not intelligent, which is another reason why you shouldn’t put too much reliance on AI outputs.
- AI is great for brainstorming, headline suggestions, creating alternative visual displays, etc. All of these things can benefit from AI assistance, but again, it’s all about the human response, and how an actual person will engage with these outputs. You need to be careful, and check over the suggestions. If you would look at the visual and be put off by its AI-ness, other people will too. AI tools are not creative, they have no creative capacity, they’re only coming up with outputs based on your query. The best ideas comes from human minds, which can be built upon with AI tools. But the human response should remain the focus.
Basically, AI, or what we’re calling AI at this stage, is not the transformative tool that some have suggested, but it will give you a lot more capacity, in a lot of ways, if you consult with AI tools as you go about your process. There are many processes that AI suggestions could help with, and some of them will be worth taking up, while others should be discarded.
But do you need to be using AI tools to excel in 2026? No, not definitively, and you may find that using the traditional approaches that you always have will deliver better results.
But you should be passing ideas through AI tools to see what they suggest, and trying out AI for ad targeting through the automated placement systems on each platform.
Experimentation is key, and you don’t need some external “expert” for that. Map out your purpose, analyze each step, and consider whether asking an AI tool might help you come up with new ways to expand on each element.
