AI helps marketers streamline, or remove internal system clutter. My focus is on how AI can help clean up the decision-making process. Teams lose potential revenue due to the way they are dealing with information, slow feedback cycles, and guessing. The steady stream of increased performance comes from creating an AI layer that ties together all the content, link, and technical health insights into one place. The true power of AI is its ability to act as a filter for removing the things you don't need to be working on. It eliminates weak signals, reinforces the core, and allows for sustainable growth that will continue regardless of changes in trends.
For industrial brands, AI in marketing matters less for creativity and more for clarity. Contractors move fast and ignore anything that slows them down. One thing that helped us was using AI to cluster job-site photos and identify which tools were used most often. That data reshaped our product education pages and cut bounce rates across key categories. Use AI to analyze field photos or service logs it reveals real usage. Focus your messaging on the top 20% of tasks customers repeat daily. Build content that answers Will this save me time? Review AI findings with people who work in the field for accuracy. When AI shows you how work actually gets done, your marketing becomes practical and practical messaging is what busy teams trust.
AI changed how I approach SEO completely. I started using these tools to track Reddit trends, which lets me tweak our content on the fly. Now when a topic starts heating up, I can jump in with a solid answer before anyone else does. The weird thing is, we started showing up in Google's Discussions panel - something I never expected. It's amazing how fast you can gain visibility when you catch these trends early.
Here's my take. My startup uses AI to make videos, and we helped a sports team automate their game highlights. Their online engagement exploded. Maybe other approaches work, but for marketing that needs to move fast, AI video is what gets results. If you're going to try it, start with short video edits. They're the quickest way to get feedback and engagement.
At Tutorbase, I found that using AI to group customers worked better than I expected. We discovered language centers that all bought at the end of the quarter, so we started showing them demos right before then. Response rates shot up. It's not magic, but it beats sending the same email to everyone. If you try this, start with a small group and see what the data actually tells you.
Working with cosmetic surgeons, I found a simple approach. Pair smart ads with specific patient data and your phone starts ringing. The challenge is people are careful about who does their surgery. We use a basic CRM to send follow-up messages that make people feel heard, which keeps them coming back. My advice? Let AI handle the data part, but keep the real conversations for people.
From running SaaS companies, I've seen how AI tools can speed up finding new customers. We looked at a bunch of options for our sales process, and the ones that learned from user data were the best for managing leads and getting new users started. It saved our team time and let us tailor follow-ups based on what people actually did. After a few months, we were keeping more clients and signing up more. If you're thinking about making a change, try a small test first.
The current phase of my career finds me at Reclaim247, where I'm heavily involved in integrating AI with marketing and product operations across the funnel. We're currently using AI to optimise our user acquisition spend and user flow, make contextual customer experiences more personal and scalable, and run near-real-time engagement trend analyses so our team can be data-driven in a much shorter feedback loop than traditional marketing analytics. I work closely with our AI specialists to better understand how AI can benefit our digital campaigns to increase marketing spend accountability, but more importantly understand how AI can optimise these campaigns to improve and accelerate user-facing product innovation. The insights we gather are contextual to product and campaign strategy (i.e. there are identifiable optimisation opportunities that we wouldn't be able to see without AI + human insight), whether it's tuning for better conversion rate in a consumer finance journey that has thousands of touchpoints, or nailing down a scalable, qualified audience for a programmatic buy. If there's interest, I'd love to talk more about our strategy and some of the lessons learned we've encountered along the way for Solutions Review and Insight Jam readers.
I want to help organizations use AI technology to create emotionally intelligent marketing campaigns that focus on women's confidence, body image, and sensory design. Marketing should use language and visuals to affirm women's presence and experiences, rather than simply functioning as a sales tool. The team at Mermaid Way uses AI to detect emotional patterns that reflect what women truly desire from their physical appearance, clothing, and personal narratives. Our approach centers on comprehension over traditional targeting methods. AI should be used to create branding that genuinely connects with people, not just to generate automated responses. That's where the real power lies.
In the corporate transportation world we operate in, timing and managing expectations are everything, so we use AI to predict demand around major events and automate guest communication. This has reduced the missed updates by 42% when tackling big programs and helped us tailor the message without sounding like a robot. Small and midsize service businesses, such as my communications agency, which has been in existence for 16 years, can incorporate AI without disrupting their operations or brand tone. The top misconception is that AI has replaced strategy. Compounding this misconception are the various depictions of executives watching their strategies fly out the window as they get beaten by a computer. I'm excited to share real frameworks of what's working now in 2025, and where the hype is still outpacing the returns.
The perspective Co-Wear can offer on AI and Marketing focuses on the Operational Integrity Gap. Most thought leaders talk about AI generating content; we focus on AI eliminating friction and making the supply chain verifiable to the customer. We pitch Flavia Estrada, Owner, Co-Wear LLC, on the topic: "Why AI's Highest Value in Marketing Is Proving Competence, Not Creating Content." The immediate insight is that AI has commoditized creation, forcing true brand value to be found in verifiable reality. We use AI to audit our logistics process and present that operational clarity—the 'truth' behind the shipping speed—to the customer in real-time. This addresses the core problem in the AI age: customers are starving for trust. Our expert shows how AI should be used as a transparency tool that strengthens the supply chain and allows the brand to speak with 100% factual authority, turning operational honesty into the most valuable marketing asset.
My name is Ryan Stone, I'm the Co-Founder and Creative Director of Lambda Films. Currently my role sits at the intersection of marketing and AI. In the creative industry, opinion on AI is divided with a very strong anti-AI majority. I have chosen to keep an open mind, understanding that the visual. (and video) industry has seen many 'industry killers' over the decades (centuries, if we consider cinema) and so I'm ensuring I understand AI, and where possible, integrate it into our workflows without crossing any perceived ethical boundaries. In our workflow, and for experimental purposes, we use LLMs, text-to-image generators, voice cloning, voice generation and dubbing tools, generative video and music. Happy to talk about the production and AI production process.
I use AI most effectively for its ability to cut through internal distractions while supporting rapid pace marketing cycles. I want to maintain clarity and consistency within our team, therefore I use AI to create a framework or structure, rather than constantly generating new ideas. This is evident with our product launch processes as an example. When we have one fragrance line that goes through 8 different people, we are looking at a product that has the potential to be delayed if there is even a small miscommunication between those 8 people. AI will map each process and highlight areas where communication may break down and cause delays prior to the delay actually occurring, ultimately saving teams wasted time on high volume releases. The benefit of having AI support is the stability it brings to decision-making, and the continued momentum that results from teams being able to execute their daily responsibilities with productivity, but not being overwhelmed.
AI has been termed the magic solution to every problem impacting all spheres of humanity, yet it has been nothing more than a volume multiplier of whatever is being done by humans. At Zibtek, we used an AI content engine to create and A/B test dozens of landing pages, one of which converted an impressive 42% more people than the base control. This was achieved from one test. Segmenting audiences more effectively led to 20-30% higher campaign engagement. When the data was scrubbed and a report was created from the campaign, the strategists recovered 70% of time and hours lost from testing. One time, a retailer working with us balanced the ad spend by time of day and observed a 25% increase in ROAS. These are not vanity wins. All of them create more value, more attention, a higher lifetime value, and faster learning. More profitable outcomes result from all of them. Start small, track business outcomes, and minimize trust risk. Transparency and data ethics are fundamental. This is when marketing is transformed from predicting to actually offering what people want, and this is what happens when human imagination is combined with AI.
The most significant impact that AI had on our content creation process was when it started helping us keep consistent messaging at scale. There are many companies who pay a lot for brand assets that have no idea what they're saying because their message has changed as different people write about them in different regions. The biggest asset we got out of AI was its ability to be a gatekeeper to the message and keep our brand's voice consistent across all of our campaigns, whether we were producing 1 asset or 200 in one month. One fintech client was able to reduce the amount of assets that were rewritten due to message drift to less than 5% after using AI for structured briefs with specific language and boundaries for each campaign. What's the true value of AI? It provides you with a stable brand voice and keeps your company from wasting money on unnecessary production costs.
Most brands have a tendency to rely on AI as a means to expedite their production output; however, actual influence is created when a brand uses AI to understand how individuals shift opinion based on geographic and cultural context. The majority of the teams I worked with at emerging tech companies said that audiences are responding to emotion they recognize, not to slick automation. One blockchain startup was able to raise $20 million using a model based on sentiment patterns from 150 placements across various tech outlets that told them which way to spin the message in order to build trust with those markets. The AI also provided the marketing team with an understanding of the signals that would require nearly 200 hours of manual analysis. When marketing teams use AI to learn about how their target audience behaves versus relying on generic data sets, they gain a competitive advantage that may seem minor but is clearly identifiable and is difficult for their competitors to replicate.
Our team loves going hyperlocal. This marketing strategy allows regional suppliers like us to compete with national brands. By using AI to create hyperlocal SEO content with suburb-specific information, local slang, and regional data, smaller brands can outrank larger competitors in local searches. AI can easily optimize content based on what products, specifications, and use cases perform best in specific towns, seasons, and industries. This perspective offers practical insights for marketers looking to leverage AI for competitive advantage rather than just efficiency.
I have personally seen AI entirely transform the concept of the communication between us and the clients in the insurance field, and frankly, the majority of agencies are still taking it as a fancy chatbot. Automation is not the real opportunity, but sizeable human-driven personalization without sacrificing the human touch that wins deals. This is what I am talking about: we are analyzing thousands of client interactions using AI and recognizing repetitive patterns in what aids the actual decision-making on enrolling. It turns out that people will not be interested in the specifics of the policy until you have addressed their fear in particular. One family is a young family, anxious about astronomical expenses. A 62 year old is interested in bridging to Medicare and not paying excessively. With AI, we are able to divide these issues prior to the initial interaction itself. The tricky part? Robotic content can be smelled by the insurance buyers at a mile distance. We have had to learn to code our systems to write the way our real agents speak, with the pauses and clarifications that the real human beings require. I am experiencing 40 percent more engagement when our email sequences are written as though they are written by somebody who has a clue about the market quirks of Arizona. The point most marketers are missing is the fact that AI is supposed to make you more accessible and not efficient. We invoke it in order to receive better and quicker answers, but even every substantive judgment is channeled through a licensed agent. There lies trust and trust is what transforms a lead to a ten years client relationship.