ET Bureau had an insightful interaction with Julian Mulhare, Managing Director, EMEA at Searce, to understand the driving force behind AI adoption in enterprises.

ETBureau: What are the primary drivers behind the rapid adoption of AI in enterprises today, and what are the key areas of Generative AI integration?

Julian Mulhare: It may seem AI is everywhere these days, and in some respects, it's true. The widespread traction in the public domain of GenAI chatbots such as ChatGPT and Gemini has done more to grab everyone's attention than any tech marketing campaign could possibly do.

A magical tool that can both "Create an essay on the history of the Punic Wars as if I was a 15 year old student", or "Summarize my meeting notes and make three strategic recommendations to improve our marketing strategy" is always going to spread around the world.

AI revenues have been steadily increasing by 40% year over year, driven by continuous technological advancements. While the release of ChatGPT marked a pivotal milestone, it was the culmination of a broader wave of sustained growth.

Organizations are leveraging GenAI across a diverse range of applications. Recent research illustrates that customer service tools are leading the charge with a 68% adoption rate, followed closely by internal research tools (60%) and content generation (53%).

Marketing and sales see a 46% adoption, with coding at 41%, and data analysis and capture at 42%. These figures highlight the large impact of Generative AI technology in streamlining workflows across various departments.

ETBureau: What are the most common maturity gaps in AI implementation, and how can businesses leaders address these to maximize their AI investments?

Julian Mulhare: Our research finds that organizations frequently focus on short-term low-hanging fruit, rather than having a long-term strategic plan.

An example of this is that they procure AI chatbot licenses for employees but fail to provide adequate training that would allow each person within the organization—whether it's sales, marketing, finance, or HR—to use the chatbot efficiently in line with their needs and roles.

While this can certainly deliver efficiency gains, it significantly reduces the ROI. It may also deepen executives' skepticism regarding AI's legitimacy, potentially damaging the chances for future AI projects to flourish.

Similarly, many organizations struggle to define the use cases that AI can address or to identify the current costs of completing these tasks without AI.

The end result is that companies are not quite sure of all the steps required to complete something as simple as a proposal to a customer, the human latency touch points between the various contributors, the time taken to author the proposal, nor how finally approved content can be ingested back into the data store for future reuse.

It's critical business leaders know their business and have the standard operating procedures (SOPs) documented, showing the interplay between individual teams and technology. This allows them to identify AI use cases and calculate the current state costs required for any future AI implementation business case.

Many organisations may not have SOPs or in-house talent to document them. At this juncture, they will benefit from using an external expert, who—in addition to understanding how to capture the existing company process flows—will be able to share additional use cases from their vast experience working with similar companies.

The final element to consider is the nature of AI investments. While these investments can be significant and weren't typically budgeted for in the past, most companies lack the in-house talent to implement AI effectively.

Partnering with a third-party provider with deep expertise and a proven approach can help companies maximize their investment. A third-party specialist can tailor a business case around the organization's unique needs, ensuring the full benefits of AI are realized. This helps avoid the common pitfall where promising technologies fail to live up to the hype due to poor implementation.

ETBureau: When deciding between building AI solutions in-house or purchasing them from external providers, what key factors should organizations consider?

Julian Mulhare: The choice of building in-house or purchasing off-the-shelf is much the same as the choice of developing applications and software in-house or purchasing externally.

A major consideration is whether the company has the internal talent to build AI solutions. For many organizations, this remains a challenge. Buying a pre-built solution often means getting to market faster, but it may not align perfectly with the company's existing processes.

On the other hand, developing a custom AI solution can be expensive and time-consuming, but it's tailored to the company's specific data and workflows.

The other key factor is return on investment (ROI). For example, in a large organization, if an AI tool saves employees 1 hour per week per person, this time-saving can add up significantly, making the investment worthwhile. Custom-built solutions can also reduce the need for retraining and process changes since they fit more naturally into how the company already operates. In contrast, pre-built solutions may require the company to adjust its ways of working to fit the software.

Overall, smaller firms often lean towards pre-built solutions because they're easier to implement, while larger companies might take a hybrid approach. They may use pre-built tools for specific needs but also develop custom AI solutions for their core operations, maximizing ROI by scaling them across the organization.

ETBureau: How can businesses assess their readiness for either approach?

Julian Mulhare: Developing AI internally requires a broad range of skills, from the initial planning and design stages to testing, development, and ongoing support. These projects can take months, so it's important to make sure the company has enough talent and the right kind to see it through.

One challenge is that once the project moves from development to the support phase, you may no longer need the same level of expertise. If you don't have new AI projects for that team to work on, you might end up with staff you don't need, which can lead to redundancies.

That's why larger organizations tend to take a hybrid approach. They might buy some off-the-shelf solutions for quick wins while also investing in internal AI development. Since they have the scale, their internal AI teams can stay busy with new projects over time, making it a more sustainable option for them.

ETBureau: What major developments in AI use can we expect to see in the next year, and how should businesses prepare?

Julian Mulhare: AI will continue to become a bigger part of our everyday tools – and lives – whether it's something we've used for years like Salesforce or Gmail, or new AI-powered versions. Natural Language Processing will make interacting with systems even easier, meaning you won't need to know technical commands like SQL queries to get the information you need.

Looking at the bigger picture, according to the World Economic Forum, 44% of workers' skills will be disrupted in the next five years. The International Monetary Fund (IMF) also estimates that almost 40% of jobs are impacted by AI, and this rises to 60% in more advanced economies. So, it's clear that businesses need to invest in upskilling their workforce, especially in areas like creative thinking, cognitive skills, and tech literacy.

Companies that fall behind in preparing for these changes could struggle against AI-powered competitors. This might sound overwhelming, but let's not forget other major shifts we've seen and conquered before. In the mid-1980s, PCs became essential for business, transforming how we worked and communicated. The difference now is that the software we already use is just getting smarter, so the transition might actually feel more seamless.

Conclusion

As enterprises navigate the complexities of AI adoption, leaders must take a strategic, informed approach. With the right strategy and support, organizations can not only overcome existing challenges but also position themselves at the forefront of an AI-driven future, ensuring they fully realize the benefits of this powerful technology.