Many companies are jumping into AI, but not all are hitting the mark. The rush to adopt AI has led to numerous projects getting abandoned, often blamed on humans rather than the technology. Recent data shows that stalled AI efforts usually stem from poor planning, mismanagement, and not enough resources. Top executives’ eagerness to become “AI-first” puts pressure on IT teams, who might not yet have the right budgets, systems, or tools in place. As IT leaders gain more experience with AI, they’ll get better at managing these projects. Jack Gold, an analyst, compares it to past tech challenges like early databases or the move to web apps, noting the learning curve is just steep.

Venture capital firms play a key role in validating AI technology. They often work closely with startup founders, attending meetings, helping develop prototypes, and guiding companies. But VCs and CIOs tend to see AI risks differently. A CIO might worry about job security or company stability, which influences how they approach AI projects. To get insights on how to succeed in AI, Computerworld spoke with several VCs about what companies should focus on.

Understanding AI’s Impact on Business

AI is changing how businesses operate. It’s not just automating tasks but transforming entire structures, workflows, and organizational charts. Sandhya Venkatachalam, a partner at Axiom Partners, explains that AI is producing results that were once only done by humans. For example, customer support is one area seeing big changes. Call centers now use AI to answer calls, cutting costs and increasing efficiency. This kind of disruption will only grow, potentially replacing legacy systems and outdated processes.

Businesses need to see AI as a tool for long-term change. Instead of focusing solely on current needs, companies should think about how AI can reshape their industry in the future. Building internal tools or proprietary systems might seem appealing but can be a waste if they replicate what large research labs already offer. AI tools evolve rapidly, roughly every six months, so the emphasis should be on strategic outcomes rather than chasing the latest tech fads.

Partnering and Strategizing for AI Success

Speed is crucial in AI development. Large organizations often struggle to keep up with the fast pace of AI innovation. Partnering with startups that are AI-native can help. These smaller, agile companies move quickly and bring innovative solutions that big companies might take years to develop internally. Harrison from Scout Ventures points out that investing in such startups can save time and money, especially for first-time AI projects.

Aligning AI efforts with industry-specific needs is also vital. For example, Harrison’s firm invests in AI applications for defense and law enforcement, where real-world results are critical. Moore from Breakout Ventures focuses on sectors like pharma and biotech, where AI is turning companies into data-driven organizations. In these fields, AI isn’t just a tool; it’s essential for staying competitive.

Creating a culture that embraces AI is a major challenge. Younger workers, especially from Gen-Z, tend to view AI tools differently than older leaders. Harrison suggests that leaders should engage directly with their teams on AI projects and give employees space to experiment. This hands-on approach fosters innovation and helps break down resistance.

Lastly, companies need to get their hands dirty. Encouraging internal prototyping and experimentation keeps organizations ahead of the curve. Mannes from Basis Set Ventures emphasizes the importance of trying out different tools and learning from failures. Teams that test and build their own solutions develop valuable expertise and trust, making them better prepared for future AI challenges.

In the end, success in AI isn’t just about technology. It’s about understanding its impact, building strategic partnerships, fostering a culture of innovation, and focusing on long-term goals. Companies that approach AI with a clear vision and willingness to experiment will be best positioned to thrive in this rapidly evolving landscape.

Inspired by

• https://www.computerworld.com/article/4093768/how-it-leaders-can-build-successful-ai-strategies-the-vc-view.html

Sources

• gmpg.org
• breakout.vc
• axiompartners.vc
• scout.vc
• circle8group.com