Nobody Knows How to Build with AI Yet

Nobody knows how to build with AI yet is reshaping industries and capturing attention across digital platforms. Here's what you need to know about this emerging trend.

I've been noticing an intriguing trend lately as I dive deeper into the world of artificial intelligence: despite the rapid advancements in AI technology, a staggering number of organizations and individuals still seem to be grappling with how to effectively build and implement AI solutions. This isn't just a minor hiccup; it's a massive disconnect between the hype surrounding AI and the practical know-how required to make it work. For instance, I recently attended a tech conference where several AI startups showcased their innovations. While the products were impressive, I overheard countless conversations among attendees expressing confusion about how to integrate these AI solutions into their existing workflows. It's as if we have all the ingredients for a gourmet meal, but no one knows how to cook! This realization got me thinking: why is it that, in 2024, we’re still struggling to figure out how to build with AI?

The Current Landscape: AI Adoption vs. Execution

The landscape of artificial intelligence is evolving at breakneck speed, and while 2024 was about bringing AI into everyday use, 2025 is projected to be about making it smarter, more ethical, and more multi-functional. According to ICONIQ's 2025 State of AI report, the focus is shifting from simply adopting AI to understanding the "how-to" of AI execution.

Examples from Different Industries

1. Healthcare: Let’s look at AI in healthcare. AI technologies have the potential to revolutionize diagnostics, treatment planning, and patient management. However, a report from McKinsey found that while 92% of healthcare organizations are interested in AI, only 27% have moved beyond pilot projects. They have the data and tools, yet many are still unsure of how to effectively incorporate AI into their systems.
2. Finance: In the finance sector, firms are experimenting with AI-driven algorithms for trading and risk assessment. However, a survey conducted by Deloitte revealed that 60% of financial institutions struggle with data integration and quality issues. They have the AI systems in place, but the foundational data infrastructure is lacking. Without that, their AI initiatives often stall or fail.
3. Retail: Retailers are deploying AI for inventory management and personalized marketing. Yet, a report by Gartner found that 57% of retail leaders feel unprepared to scale their AI initiatives. This is partly due to the complexities involved in understanding customer behavior and integrating AI with existing customer relationship management systems. These examples highlight a common theme: organizations are excited about the potential of AI but lack the necessary skills and frameworks to build and scale effective AI solutions. This gap is contributing to the narrative that "nobody really knows how to build with AI yet."

Why This Trend Matters

Understanding this trend is crucial for several reasons:

1. Competitive Edge: As AI becomes more ingrained in business operations, organizations that can effectively harness AI will have a significant competitive advantage. A recent study by PwC predicts that AI could contribute up to $15.7 trillion to the global economy by 2030. Those who learn to build with AI now will be positioned to capture that value.
2. Job Market Evolution: The skills needed for AI development and implementation are evolving. According to the World Economic Forum, by 2025, 85 million jobs may be displaced due to the shift in labor between humans and machines, but 97 million new roles will emerge that are more adapted to this new division of labor. This means that individuals who invest in understanding how to build with AI will be better equipped for the future job market.
3. Ethical Considerations: As AI systems become more prevalent, ethical considerations must also be addressed. Without a solid understanding of how to build and implement these systems responsibly, organizations risk creating biased or harmful AI solutions. This is particularly relevant in sectors like criminal justice and hiring, where AI can have significant societal implications.

Predictions for the Future of AI Building

As we look ahead to 2025 and beyond, I think we’ll see a few specific trends emerge in how organizations approach building with AI:

1. Increased Focus on Education and Training: Organizations will invest more in upskilling their workforce. Expect to see a surge in online courses and certifications focused on practical AI skills. Platforms like Coursera and edX are already seeing increased enrollment in AI-related courses, indicating a shift toward practical knowledge.
2. Collaborative Ecosystems: We may witness the rise of collaborative ecosystems where companies partner with AI startups, educational institutions, and research organizations to co-create AI solutions. This could lead to more robust frameworks for building AI, leveraging shared knowledge and resources.
3. Regulatory Frameworks: As AI adoption increases, governments will likely step in to create regulatory frameworks that guide ethical AI development. This could help standardize best practices and provide a clearer roadmap for organizations looking to implement AI responsibly.
4. AI Toolkits and Frameworks: We might see the development of more user-friendly AI toolkits that simplify the building process. Companies like Google and Microsoft are already working on cloud-based AI solutions that allow businesses to implement AI without needing extensive technical expertise.

Conclusion: Time to Take Action

In summary, the fact that "nobody knows how to build with AI yet" underscores a critical gap in our understanding of this transformative technology. As we move into 2025, it’s imperative for organizations and individuals alike to bridge this gap. By investing in education, creating collaborative ecosystems, and developing ethical frameworks, we can collectively figure out how to build with AI effectively. If you’re reading this and feel overwhelmed by the AI landscape, I encourage you to take actionable steps. Start by exploring online courses, connecting with local AI meetups, and diving into AI projects, even if they’re small. The sooner you begin understanding how to harness this technology, the better positioned you will be as we navigate this new frontier together. So, what are you waiting for? Dive in and start exploring the world of AI. The future is here, and it’s time to build!