Five strategic AI shifts expected to transform business by 2025

 

A major transformation of global business is on the horizon, driven by five strategic shifts in artificial intelligence (AI) poised to take centre stage by 2025.

 

These shifts, ranging from the rise of domain-specific AI models to the convergence of quantum computing and AI, promise to reshape industries and economies worldwide. 

 

Juhi McCelland, managing partner of IBM Consulting, APAC, outlined these pivotal changes at Krungthepturakij's “AI Revolution 2025: A New Paradigm of New World Economy” forum on Thursday.

 

McCelland detailed five strategic AI shifts poised to redefine the business landscape:

From Generic to Domain-Specific Models: The focus is shifting from large, multi-purpose language models to smaller, purpose-built models tailored to specific industries. 

 

"You don't need to know what somebody in Telco is doing if you're a cosmetic company,"  McCelland explained, highlighting L'Oreal's use of AI for personalised beauty experiences as an example.  

 

She also cited the Hong Kong Jockey Club's AI-driven system, which now delivers detailed horse racing information to fans in minutes, a process that previously took 48 hours.  

 

Juhi McCelland

 

The Rise of Agentic AI: This involves autonomous collections of AI agents designed to solve complex business problems by breaking them down into smaller, manageable tasks. 

 

"Agentic AI is an autonomous collection of different agents, searches, and things that can solve real business problems," said McCelland. 

 

She noted IBM Consulting's use of agentic AI to assist its consultants and Riyad Air's deployment of the technology to accelerate the launch of its new digital-native airline. 

  

 

Open and Hybrid AI: McCelland stressed the necessity of partnerships and a hybrid approach to AI, acknowledging that data is distributed across public clouds, private data centres, and sovereign clouds.

 

"You have to do a hybrid approach by design because right now it's happening by accident," she stated. 

 

She also referenced a study in Thailand indicating that a lack of trust in data is a significant impediment to AI deployment.

 

The Centrality of AI Governance: McCelland emphasised the critical role of robust AI governance in ensuring data trustworthiness, fairness, and compliance.  

 

She advocated for governing AI models and establishing internal governing bodies within companies to define ethical standards and policies. 

 

Quantum and AI Convergence: McCelland highlighted the complementary nature of quantum computing and AI, projecting that quantum computing will become more accessible for business applications by 2030.  

 

She cited examples such as JP Morgan's use of quantum computing for financial modelling and Cleveland Clinic's exploration of technology for drug discovery.  

 

McCelland also issued a warning about the need for "quantum-safe" strategies to protect data from potential quantum computing-based security threats.   
 

 

 

In her broader remarks, McCelland acknowledged the rapid growth of AI, spurred by large language models like ChatGPT, but cautioned against uncritical adoption.  

 

"AI is currently used as a Swiss Army knife... It's young, it's energetic, it's exciting,"  she said, underlining both its versatility and potential pitfalls. 

 

She also stressed that "only 1% of business data today in this world in 2025 is being used for generative AI," indicating the vast untapped potential of the technology.

 

McCelland also addressed the growing importance of AI regulation, noting the efforts of the EU and other governments to balance innovation with risk mitigation.  

 

She emphasised that businesses are increasingly focused on demonstrating a clear return on investment (ROI) for their AI initiatives.

 

McCelland highlighted AI's potential to significantly boost the global economy, citing projections from McKinsey that it could add between $2.3 and $4.4 trillion in profits annually. She also pointed to PwC estimates that suggest AI could contribute $15.7 trillion to the global economy by 2030.

 

Looking ahead, McCelland reiterated IBM's commitment to responsible AI development and its role as a trusted partner in driving business transformation. She drew on IBM's partnership with Ferrari in Formula 1 to illustrate the crucial role of data and technology in gaining a competitive edge. 

 

"In one second, a Formula 1 car produces 10,000 data points," she noted, underscoring the importance of leveraging data for success.