Everybody is using AI, but here’s how companies can use it more effectively

November 11, 2025• byChris Peters

Companies are moving beyond AI pilots, but they are stuck at a bottleneck

With the hype surrounding AI over the past few years, it has also generated considerable noise, accompanied by lofty promises of breakthroughs. Whether you are pro or anti-AI, it is undeniable that the technology has changed the way we function, and businesses should also acknowledge it.

According to a recent report by Bain & Company, CEOs in Southeast Asia have moved beyond the training stages, with billions of dollars being invested in data centers and infrastructure to power through the next wave. However, a one-size-fits-all AI solution doesn’t exist, and multiple factors need to be considered before making a decision.

Vulcan Post has reviewed the report, and here are three steps that can help CEOs develop a better AI strategy.

1. Pick only 2-3 main areas where AI can help your business

CEOs need to view their operations and plans from an outside-in perspective to better adapt to potential advancements in the customer experience through three primary forms of disruptions:

AI customer agents that would make low-brow decisions on behalf of the human behind it.
Autonomous physical operations where systems—such as robots and drones—can automate heavy-lifting industries, including logistics, agriculture, and mining.
Using real-time intelligence to simplify, speed up, and improve business outcomes.

However, successfully evaluating from a bird’s-eye view is only half the battle won; CEOs should choose two to three areas, from enhancing efficiency to lowering costs, where AI can fundamentally change how they compete in their respective industries, rather than implementing a full-blown AI strategy without a clear focus.

In one case study by Bain & Company, the company helped an engineering, procurement, and construction firm create an AI strategy that strengthened its competitive advantage. They harnessed efforts to achieve a single goal: reducing costs and increasing productivity by focusing on high-impact AI use cases.

Two main solutions were then developed to streamline operations: a Project Management Assistant that provides real-time project performance visibility and recommendations for project leaders to correct course when needed, as well as supply chain AI solutions to empower procurement teams to make sourcing decisions more efficiently.

With any AI-based business solution, CEOs must understand that AI will impact the business on a macro level. However, instead of implementing the technology across the board without careful consideration, focusing on key areas to gauge its impact is a more prudent method. Expansion may happen later, when desired results are achieved.

2. Focus on speed & responsiveness

CEOs should also set goals around speed and responsiveness by automating time-consuming tasks such as data gathering and analysis.

A life sciences company that collaborated with Bain & Company was struggling to stay updated with regulations across its international markets, where it was easy to become overwhelmed with consolidating hundreds of documents per submission over months, which could lead to critical delays.

Two gen-AI tools were developed to improve its regulatory workflow and speed across filling cycles: a copilot for document extraction and Q&A, as well as a submission tool to translate and generate tailored filings by market. All that was needed was for an employee to check its work.

Once that is achieved, businesses can work on how they can utilise AI to increase overall capacity while also having leaner teams, ultimately breaking the direct relationship between revenue growth and cost increases.

3. Invest in human talent AND data

However, this study isn’t meant to suggest that AI will take over all operations. Companies need to hire new staff to reinvent core processes and introduce technical solutions, while also upskilling existing employees to identify opportunities and integrate AI into their day-to-day work.

CEOs should also invest in data, as the quality, availability, and usability determine the scale of the transformation, and they account for more than half of the heavy lifting. Instead of working towards a “perfect” data set, the most effective way is to work backwards from high-value use cases to build their backbone.

A pharma and healthcare firm struggled to turn its data into insights that could boost efficiency and competitive advantage. Together with Bain & Company, the business defined a roadmap and started with finance and procurement to unlock savings opportunities, and expanded into other departments once identified.

An AI function run by 16 engineers was also launched, which accelerated a pipeline of use cases and allowed the company to increase its annual value between US$30 million and US$50 million across the business.

Final thoughts

From ChatGPT by OpenAI to Nvidia to DeepSeek, we have seen many success stories spearheading the AI industry. However, we have also seen numerous reports of inconsistencies, and we once debated whether the AI bubble would burst.

The world doesn’t want to experience another dot.com 2.0; hence, CEOs will need to remain pragmatic in their AI strategies by not diving headfirst and understanding that there is no one-size-fits-all AI solution.