Blasé Capital AI IN ASIA

When we think of the use of Artificial Intelligence (AI), we think of America and Europe. But according to a recent survey, Asia is fast-emerging as a hub of tech adoption. A joint study by FICO and Corinium Global Intelligence shows, “Enterprises across Asia are operationalising AI at scale, balancing innovation with governance, risk management, and efficiency to drive business value.” More than seven in ten Asian firms feel that AI delivers the highest return on investment, a percentage that is higher than Europe (48 per cent), and Australia/New Zealand (44 per cent). At one level, this may indicate higher realisation, and desire to use AI. But at another one, it may show an initial enthusiasm since Asia lags Europe, where the limits of AI are becoming obvious to firms, managers, and employees. In new tech, the initial curve is steep, which plateaus, and then takes off again.

Asian firms, like their western peers, think of AI as a core business capability, which can drive customer experience, and improve revenue and market share, apart from profits. Three-quarters of the respondents in the survey believe this. But what is more crucial in the thinking among Asians is the emphasis on AI-linked governance, apart from just business, financial, and productivity outcomes. The study, which surveyed senior AI and data leaders across five regions such as North America, Latin America, Europe, Asia, and Australia-New Zealand, finds that the Asian firms end to take a more “structured, risk-free approach to scaling AI than their global peers, underscoring stronger focus on transparency, control, and predictability.” Responsible AI standards, and intelligence systems feature prominently. This may either hint that the Asians are more risk-averse and cautious, and not overwhelmed by AI, or their financial constraints force them to look for wider improvements, rather than narrow and limited results.

Key insights from the survey include the Asians’ focus on efficiency, as 83 per cent of Asian firms cite cost savings, and process efficiency as the main catalysts for AI. A minority believes in business alignment with business goals, which is completely missing from the European peers. More than three-fourths of Asians highlight governance gaps, and feel that “inadequate AI model monitoring is the biggest barrier” to scale up AI. This implies that rather than herd-based and blind adoption, the focused outcomes are crucial. IT, risk, and compliance teams get priority among the Asian firms. This may be positive or negative. The western peers have realised (see Our Take on this page) that AI has an uneven distribution among divisions and departments. The results differ. Hence, IT and risk assessments may be important. But too much emphasis on them may delay or derail AI adoption.

According to study, the above-mentioned insights are relevant for India, “where AI is being deployed at national scale across banking, payments, and digital public infrastructure. “India is deploying AI at a scale few markets can match…. At that level of adoption, governance, monitoring, and explainability are not optional. They are fundamental to trust, regulatory confidence, and sustainable business performance,” says Dattu Kompella, MD, Asia Pacific, FICO. Other studies, like one by Stanford University, rank India third globally in overall AI vibrancy. “As Indian enterprises move from pilot programmes to enterprise-wide AI adoption, governance, monitoring, and accountability are emerging as critical differentiators in delivering sustainable return on investment,” states the survey. In other words, the hurry, excitement, and enthusiasm in India, where policy-makers think of AI, digital, and tech as mega and overall tools for effective governance, the haste may result in mistakes, even blunders, which cannot be undone later.

Of course, there are challenges (see Our Take on this page). The FICO-Corinium survey highlights the problem areas. Resistance to change, espoused by 71 per cent of the respondents, remains the oft-quoted barrier. In the banking sector, where unions opposed computers and software, AI is the most feared tool among the employees. There is limited collaboration between business and IT teams. This is always the case, especially in emerging economies, where the two work largely in silos, do not talk to each other, and even hate each other’s guts. Business divisions think that IT is out to get their jobs. IT thinks of business as stupid, naïve, or innocent, who have no idea of the future. Almost two-thirds of the respondents in the survey feel that there is a lack of shared understanding about AI. Like mentioned earlier, different departments, and sets of employees view it differently. Hence, there is a need for cross-functional, and cross-discipline alignment within firms.

In essence, if AI needs to become the norm, rather than exception, or if it needs to be used rather than be paid lip-service to, firms in Asia, and other regions, must focus on better models, or rather more relevant models that have narrower views and depend on small-language models. In addition, the management must evolve “stronger standards, smarter systems, and deeper collaboration across the enterprise.” Responsible AI, not Responsive AI, needs to be the norm, as Asians believe in adherence to formal standards, and ranks second globally behind North America. The two indicate an advanced approach to Responsible AI.