Executive-Level Figures Ponder the Financial Consequences of AI as the Festive Season Approaches
The whirlwind of AI enthusiasm has left many C-suite executives spinning. If you've lost count of how many announcements came from AWS's re:Invent 2024 conference, you're not alone. Microsoft's OpenAI wasn't about to be outdone and announced their "12 Days of OpenAI", with CEO Sam Altman posting on X, "Each weekday, we will have a livestream with a launch or demo—some big ones and some stocking stuffers ... we’ve got some great stuff to share, hope you enjoy! Merry Christmas."
For the past two years, I've been advising, speaking, podcasting, and reporting on the AI revolution that's turning traditional business strategies on their heads. There are countless automation technologies that are currently being evaluated in C-suite meetings and boardrooms worldwide.
From intelligent chatbots to predictive algorithms, companies have been attempting to enhance their competitiveness and operations, but the impact on the bottom line has been minimal.
There are numerous reports and studies discussing the enormous potential of AI, what it will look like in the future, and several projections suggesting it will contribute $15 trillion to the global economy by 2030. The smart leaders are looking at AI strategically, as a new frontier for not just survival but to thrive and develop entirely new business ventures and even new sectors.
These are exciting times. However, my question persists: How can organizations actually leverage AI to boost growth and financial ROI outcomes?
What Gets Measured Gets Done
Numerous vendors are taking on this challenge, leveraging advanced AI and machine learning technologies to drive innovation across various industries. One tech company investing heavily in building proprietary AI and amplifying business outcomes through tailored AI-driven solutions is Tech Mahindra. With strategic partnerships, including collaborations with NVIDIA, the company is dedicated to accelerating AI adoption in emerging domains like Generative AI and Quantum Computing.
I recently spoke with Lakshmanan Chidambaram (CTL), President and Head of Americas Leadership Council, Tech Mahindra, and Americas Head, Mahindra Group (M&M.NS), to understand how they are helping businesses unlock the financial potential of AI. Many leaders, like Chidambaram, believe that AI's potential extends far beyond cost-cutting and is more about unlocking efficiencies, entirely new growth categories, and more profitable business models.
AI has undeniably generated significant excitement, with industry leaders touting its transformative potential. As AI models become faster, smarter, and more reliable like SLMs, organizations are racing to capitalize on these significant investments.
But again, how can the return on investment (ROI) match these lofty expectations? I asked Chidambaram, “The answer lies in AI’s ability to evolve beyond isolated functions, like chatbots or customer service automation, and become a comprehensive tool integrated into core business processes. Take the financial services industry, for example; with a robust, enterprise-wide AI strategy, it is possible to achieve up to 40% higher ROI than those with fragmented efforts. Successful ROI from AI requires strategic alignment across all business functions.”
Moving From Experimentation To Creation
According to estimates, the global manufacturing industry was valued at $3.2 billion in 2023 and is expected to see the largest financial impact due to AI, with the sector expected to reap a gain of $20.8 billion by 2028. AI has the potential to drastically alter the sector's economic impact. The same report highlights that by integrating AI to predict equipment failures and automate routine quality control checks, enterprises have reported a 40% reduction in downtime and an almost 15% increase in overall productivity. This directly translates into cost savings of over $100 million annually.
The key to achieving real ROI from AI investments lies in its integration with automation at scale. From multi-national OEMs like GM to mid-cap providers like PBC Linear, manufacturers are embracing AI-driven automation to revolutionize their assembly line operations. By leveraging automation and cobotics with AI, manufacturers are beginning to streamline their operations, improve product quality, and minimize costly errors.
Commenting on ways these companies can measure AI ROI, Chidambaram said, “It is time to move from experimentation to value creation. To ensure that AI investments pay off, businesses need concrete methods to measure success. One approach, derived from an AI verification tool used across multiple industries, focuses on four key metrics: operational efficiency, cost savings, revenue generation, and customer satisfaction.”
Auditing AI Validation, Assurance, and Governance
Tech vendors are working to develop tools that help companies ensure robust validation and governance across the entire lifecycle of their AI projects. CTL's company recently launched TechM VerifAI, an automated framework for validating AI systems in real-time, for compliance with industry standards and regulations.
It is a comprehensive validation framework across the GenAI lifecycle, with customizable metrics, microservices-based architecture, which can integrate into existing technology stacks to enhance AI value realization for enterprises. This is important because it starts with validating data quality in the discovery and pre-development stages—followed by testing AI models, frameworks, and hyper-parameters in the actual development stage to ensure security and accuracy. You might want to re-read that, because companies have sometimes skipped those early steps only to reboot and restart AI projects later.
Broadening these contemporary challenges, Chidambaram concurs, "Most businesses have yet to progress from AI trials and tests to enterprise-level integration of AI, mainly due to the lack of a strong validation and reliability system. We tackle this issue by proposing a comprehensive evaluation, audit, and certification system for AI solutions, enabling businesses to responsibly utilize AI for growth, prosperity, and expansion at an accelerated pace, by automating their validation and verification procedures."
Optimal Approach to Amplifying AI Investments
AI integration should extend beyond individual departments and into the company as a whole. By combining AI with both customer-oriented operations and back-end processes, businesses can generate value at every point of interaction. Moreover, AI should not be perceived as a solitary venture or experiment in technology. Instead, AI projects should be aligned with broader corporate goals, such as enhancing customer loyalty, minimizing expenses, or expanding into new markets.
The most substantial gain from AI results from tailoring AI solutions to meet industry-specific requirements. For instance, in retail, AI can fine-tune pricing and promotions according to real-time demand forecasts, while in agriculture, AI-guided drones can enhance crop yields by monitoring field health. AI systems need to perpetually train, fine-tune, and adapt as business scenarios shift. This ensures adaptability and allows businesses to seize emerging opportunities.
From AI Potential to Organizational Outcome
The potential of AI is indisputable, but its true worth lies in its ability to aid senior executives in achieving financial gains beyond mere technological innovations. In today's swiftly evolving market, where businesses face mounting price pressures, talent deficits, and fierce competition, AI offers a route to sustained growth and profitability. However, the key to tapping into this value is to strategically incorporate AI into the organization, persistently assess its influence, and align it with key corporate objectives. With the appropriate strategy, AI transforms into an empowering market driver—and, even more crucially, a profit booster.
- Despite the hype around AI at AWS re:Invent 2024, many C-suite leaders are still struggling to leverage AI to boost their financial ROI outcomes.
- Tech Mahindra, led by Lakshmanan Chidambaram, is investing heavily in building proprietary AI to amplify business outcomes for its clients.
- General Motors and mid-cap providers like PBC Linear are embracing AI-driven automation to revolutionize their assembly line operations and boost productivity.
- According to Chidambaram, successful ROI from AI requires strategic alignment across all business functions and a shift from experimentation to value creation.
- Tech Mahindra's TechM VerifAI is a comprehensive validation framework that helps businesses ensure compliance with industry standards and regulations in their AI projects.
