Integrating AI Into Work: Start-Ups May Have an Advantage

Start-ups lack barriers that could affect effective deployment of AI.

Reviewed by Abigail Fagan

Key points

• Start-up can more easily deploy AI due to their flexibility and lack of legacy systems.
• Integrating AI expertise from the start helps ensure seamless adoption in start-ups.
• Start-ups must balance AI innovation with caution to avoid ethical and financial pitfalls.

Artificial intelligence (AI) is here to stay, and it’s likely to only improve as time rolls on. Many organizations and professions, though, have wrestled with how to leverage it[1]. I’ve documented some of the potential issues and challenges in the quest to use AI effectively and ethically, from questionable predictions[2] to a lack of expertise to challenge AI outputs[3] to the potential for AI to manipulate our choices[4]. These are all very real concerns that must be addressed as more organizations, industries, and professionals seek to integrate AI into their work.

However, Briggs and Briggs (2024) recently shared an excerpt of their book on Big Think. In it, they discussed how start-ups can greatly benefit from advances in AI and provided a list of potential sales and marketing use cases. Their article is well worth the read, but what I wanted to do here was to discuss the reason why start-ups, as opposed to existing organizations, are likely to benefit more from AI.

Start-Ups Lack the Same Barriers

Start-ups are uniquely positioned to benefit from AI advancements because they often start with a blank slate when it comes to structure. Established organizations typically possess legacy systems, pre-existing work processes, and an ingrained culture, which makes for greater resistance to change (Khaw et al., 2022). The larger the change, the more difficult it is to implement successfully. Even when bigger changes are successful, they often require a great deal of time and effort to ensure they run smoothly and are institutionalized. This can be quite a challenge.

We’ve seen this firsthand with remote work. Many organizations responded to COVID by simply migrating existing processes, policies, and workflows to a remote work environment, rather than following the advice of experts[5] who’ve advocated for the benefits of strategically re-thinking how work is accomplished. Many simply cannot move past their bias toward the standard way of working. But seeking to force that way of working onto employees, many of whom have had a frame of reference shift since the pandemic, can lead to a disconnect between what the organization “requires” and what managers permit (as I discussed in a recent post).

On the flip side, start-ups have the flexibility to design their operations from the ground up. They’re not trying to retrofit new technology into existing structures and processes that simply weren’t designed to capitalize on the benefits various AI tools can provide. As such, start-ups can integrate AI in ways that are more seamless and innovative, allowing them to take better advantage of AI’s benefits.

Start-Ups Are More Agile

One of the most significant advantages that start-ups possess when it comes to AI integration is agility. In contrast to established organizations, which often possess larger hierarchies and layers of decision-making, start-ups can pivot quickly, experimenting with AI tools and technologies without being bogged down by cumbersome approval processes. This agility allows them to test, iterate, and refine AI applications rapidly, leading to faster innovation and a competitive edge in the market (Kim et al., 2024).

This nimbleness is not just about speed—it’s also about openness to new ideas. Start-ups are often founded by individuals willing to challenge the status quo and explore unconventional approaches. This mindset can lead to greater acceptance of AI because it’s a new and ever-evolving technology. By being open to experimentation and willing to take calculated risks, start-ups can uncover novel applications for AI that might be overlooked by more established players.

Expertise Can Be More Seamlessly Integrated

One challenge that both start-ups and established organizations face when integrating AI is the need for expertise (Ratner Labs, 2023). AI is a complex field that requires specialized knowledge to implement effectively[6]. While larger organizations may have more resources to hire AI experts, they often face the challenge of integrating these experts into existing teams and aligning their work with pre-existing goals and strategies.

Start-ups, by contrast, can build their teams with AI expertise as a core component from the beginning. This allows them to ensure that AI isn’t just an add-on to their operations but is integrated into the core of their business model. Moreover, because start-ups are typically smaller and more cohesive, the expertise of AI professionals can be more effectively leveraged across the organization. This means the insights and innovations these experts bring are more likely to be adopted and implemented, driving the start-up’s growth and success.

But Beware of Potential Missteps

While start-ups are uniquely positioned to benefit from AI, proactive AI integration comes with risks. All the issues I mentioned at the beginning of this post equally apply to start-ups seeking to proactively integrate AI into their business. AI tools can produce biased outcomes, make incorrect predictions, and lack transparency in how they derive outputs. Consequently, there are risks that come from basing key business decisions on the outputs produced by AI tools.

This seems especially likely if AI tools are implemented to replace human expertise. While AI technical expertise can aid in the development and implementation of tools more tailored to a start-up’s needs, start-ups also need sufficient domain expertise to monitor and properly make use of the outputs produced. AI development and integration can be costly, and many start-ups operate on a tight budget. These two factors could combine to result in overreliance on the promise of AI at the expense of human domain expertise.

Another challenge is the potential for ethical missteps. Start-ups, especially those operating with lean teams and limited oversight, might inadvertently deploy AI in ways that compromise user privacy or result in problematic biases. Without proper checks and balances, start-ups are at risk of making decisions that could lead to public backlash or regulatory scrutiny.

Finally, the rapid pace of AI advancement means that start-ups must continually adapt to new technologies. This constant evolution can be challenging, particularly for start-ups that do not have the resources to keep up with the latest developments. Falling behind in AI innovation could leave a start-up vulnerable to competitors who are better equipped to leverage new technologies[7].

Conclusion: Embracing the AI Advantage

While start-ups are indeed well-positioned to capitalize on the benefits of AI due to their agility, lack of legacy systems, and the ability to build AI expertise from the ground up, they must navigate these advantages carefully. The potential for rapid innovation and competitive differentiation is immense, but so, too, are the risks associated with over-reliance on AI without a strong foundation in both technical and domain expertise. Start-ups must be vigilant in ensuring that AI is used to enhance, rather than replace, human decision-making, and they should be aware of the potential risks and challenges that AI tools can introduce.

Ultimately, the promise of AI for start-ups lies in striking a balance between innovation and caution. By being cognizant of the potential pitfalls and ensuring they have the right mix of expertise, start-ups can harness AI's power to drive growth and success. However, they must also be prepared to continuously adapt and refine their AI strategies to stay ahead in a rapidly evolving technological landscape.