Joaquín Cuenca Abela is the CEO and co-founder of Freepik, the global tech company helping people create great designs – faster.
While Elon Musk predicts that AI will soon overtake human intelligence, in reality, our sci-fi fears are likely far from happening. There is a middle ground. AI probably won’t replace a whole workforce or the need for your business, but it will transform all industries and push forward innovation. If you don’t capitalize on its power, you could miss out.
So, what’s the best way to deploy AI in your business? For some, it might be simply adopting a chatbot to streamline customer services, or using generative AI tools to brainstorm ideas. Others will want to build an AI product in-house.
I’ve worked with a team that is building AI tools to transform the way we design visual assets, and I’ve seen that the creative industry offers valuable insights for other sectors. If you’re leaning toward building your own AI products, here’s a simple guide to help you make that a success.
Foster a company culture of curiosity.
To build an AI product, first you need a team of curious, continuous learners who are willing to experiment and fail fast. The industry is changing rapidly, so there are lots of opportunities to get involved in the community, but open-mindedness is key. To foster a proactive, AI-based culture, you and your team need to:
• Stay informed: Get nerdy by following the news about AI, subscribing to newsletters, engaging with experts and reading deep into threads on X and Reddit. Also, encourage sharing across teams and the company.
• Gather feedback: Beta testing is your friend. Get valuable insights from people you trust in the AI community. You could consider setting up a partner program to do just that.
• Anticipate future trends: It’s imperative to continuously monitor advancements and predict what’s next. Here, open-source research can provide valuable insights and cost-effective solutions; however, technology can become outdated quickly, so ongoing monitoring, development and iteration are key. A “set it and forget it” approach won’t work.
• Invest in training: That doesn’t mean you have to spend money on expensive data analytics courses; it’s about getting hands-on and learning as you go. Test out different vendors; analyze competitor strategies, and do a lot of prototyping.
• Be transparent: Clearly communicate the AI roadmap and vision to get everyone on board and feeling invested in its success. This will also instill a sense of ownership among team members.
Don’t build for the sake of building.
If you’re chasing trends, you’re doing it wrong. Before diving in, pinpoint why AI is crucial for your organization and the problem you want to solve. Having clarity on your objectives is key, and make sure it’s going to serve your audience. Ensure you:
• Do your research: Explore existing solutions and assess if building custom AI fits your capabilities. Don’t forget—it’s not about adopting AI for popularity, but addressing specific challenges comprehensively.
• Focus on the customer: Ditch the “be the best” mentality, and focus on understanding your target audience’s needs. Differentiation is key, so listen closely to customer and employee feedback to find unique use cases that resonate.
• Engage all levels of the workforce: Inclusive decision-making is important because it means you have diverse perspectives. High-level discussions with the C-suite alone, for example, may miss valuable insights from those directly impacted by AI implementation.
• Assess all the options: Don’t be afraid to use external expertise and recognize where others excel. For example, rather than build an entirely new tool, my company acquired an AI company, and we’re working to enhance and build on their community.
Learn from the creative industry.
Confession time: Like many in the creative field, I was initially apprehensive about AI’s impact on design. However, witnessing how my company has integrated AI into our business strategy has transformed my perspective. AI is a collaborator rather than competitor, helping people create great designs, faster. And the story of AI in the creative industry offers a blueprint for building successful products across other sectors.
Human-centered design is paramount. By automating repetitive tasks and freeing up human creativity, AI can augment human capability, not replace it. But you need to work with customers and users to build the products they genuinely need. AI should solve real problems and deliver clear value to users.
What’s more, the design industry’s adoption of AI—like using enhancer tools or switching up styles—also highlights the power of experimentation. Rapid prototyping and user feedback loops are crucial for continuously improving AI products and ensuring they meet evolving user needs.
For those unsure where to begin, I think the creative industry’s adoption of AI can serve as a roadmap for success. By prioritizing human-centered design, focusing on value creation and embracing iterative development, businesses can build AI products that unlock new possibilities and drive growth. Making AI a part of your business may seem daunting, but if you take the leap, it could pay off.
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