Deepak Chaudhari, country head of Tata Consultancy Services (TCS) in Ireland, outlines five steps to maximise AI’s potential and prepare for the real long-term gains.
AI has dominated the conversation in business and technology for the past year, and the 2024 World Economic Forum in Davos was no exception. The conference’s AI theme reflected the focus that many of our clients have on the astounding potential of artificial intelligence.
Initial results of our upcoming TCS AI for Business study of more than 1,200 top global executives show that 55% of corporate executives are excited or cautiously optimistic about the potential of AI. At the same time, many business leaders feel overwhelmed by the scale of possibilities AI offers.
“Artificial intelligence may be the words on everyone’s lips, but leaders who want to profit from AI’s real long-term benefits must look beyond cost reduction and correctly lay the groundwork for future success”
In times of economic uncertainty, business leaders initially look for immediate ways to benefit operations, products, and customers. And, without doubt, AI offers ample opportunities to enhance productivity and reduce costs.
But starting with a technology and then seeking applications for it rarely works out. It is far better to start with a business problem and then understand what technologies or tools can best be used to find a solution. By approaching AI in that way, the technology can help businesses in both the short and long term.
Implementing AI for the long term
Most enterprises aim to be tactical with their investments into AI, and early results our AI for Business study indicate that they want to use it to replace legacy technology, lower their total cost of ownership, and speed up development time or time to market.
With predictive and analytical capabilities, AI can be very helpful with this. However, the best long-term benefit of GenAI, in particular, lies in augmenting decision making. Decision making is often heavily dependent on tacit knowledge accumulated over time – you know what to do and how to do it based on experience. AI can be a collaborative tool, helping to unearth that knowledge and digitalise some of those processes to ultimately improve decision-making.
One of our clients, a major vehicle manufacturer, already charts a collaborative path using AI for narrowly defined tasks. They apply machine learning to extract value from the data they gather from more than 500,000 connected vehicles. This can inform the work of their engineers, who use the information and vehicle data to improve customer interfaces and make vehicles safer.
In the Netherlands, a major discount retailer we work with has transformed its dynamic pricing strategy with an AI platform that replaces complex legacy systems. Where pricing was once based on spreadsheets, unordered data, and manual checking, it now relies on a live assessment of information collected by AI. The customer experience also benefits from more tailored offerings in each store.
These examples demonstrate that AI, when applied to a specific problem, can revolutionise business efficiency by extracting actionable insights from data.
AI strategies for ‘right now’
Though the future of AI is in working collaboratively with humans and supporting decision-making, short term efficiencies can also be found. However, the key is still to take a business-first perspective, rather than a technology-first one.
In practice, we recommend a five-point plan for CEOs looking to make the most of AI right away and build capabilities for long term success:
- Appoint an AI leader: appoint a single executive to take charge of AI transformation, establishing leadership and ensuring accountability at every stage of the process.
- Develop an AI strategy with guardrails: GenAI brings many advantages but is still an early-stage technology with strengths and weaknesses (data security, regulatory compliance, mitigation of bias, etc.).An AI strategy with guardrails allows enterprises to harness the power of AI while safeguarding against security breaches, compliance violations and ethical concerns.
- Adopt the right technology within a robust AI-forward framework: transformation of the legacy IT stack, operating systems, policies, and regulatory approach requires a multi-tiered architecture that extends across the business, empowering employees, partners, and customers.
- Use AI algorithms that are fit for purpose: Combine large language models with small- and medium-sized ones at enterprise or even activity levels to find the right balance between computational complexity, accuracy and efficiency.
- Invest in your workforce: Re-skilling is necessary, but not sufficient. Executives leading an organisational AI transformation must establish a culture of change to motivate their staff for rapid AI adaptation and to ensure people and machines work effectively together as technology evolves.
Artificial intelligence may be the words on everyone’s lips, but leaders who want to profit from AI’s real long-term benefits must look beyond cost reduction and correctly lay the groundwork for future success.
Ultimately, augmenting humans with AI will make knowledge more accessible and empower our creativity, productivity and decision-making power, putting us on a path to a more sustainable and competitive future.
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