We ask you instead, why not?
Artificial Intelligence (AI) is the biggest innovation since the creation of the internet and is rapidly bolstering business performance across industries. It’s likely that your organization and competitors are already seeing a positive return on investment in AI, Machine Learning and Deep Learning talent, while also stumbling upon a sparse talent pool in this space.
For example, a major challenge of AI implementation is to ensure cohesive adoption throughout the organization. This is where an AI leader could play the critical role of bridging the gap across roles and business units to foster synergy and facilitate usage. As we address in another article, success starts with a tight alignment on organizational culture.
Moreover, bringing an AI leader with a longview can help attract, develop, and retain top AI talent across business divisions and ensure the company has the necessary expertise to stay at the forefront of AI development.
Without a doubt, AI is progressively permeating every aspect of business. Manoj Narayanan, Managing Director, Technology of GTCR, emphasizes that AI has consistently been employed to construct targeted solutions based on data to or new innovations relying on availability of computing power. But as he explains, “The difference is that now we can harness AI to also drive areas vital to the broader organization like increasing operational efficiency and managing risk. If one were to add the recursive abilities of AI driven software, this has the potential to truly aid the CEO in making impactful decisions.”
Lending their technical prowess, AI leaders will steer the organization through the hurdles and wins of the implementation journey. They will identify opportunities where others see roadblocks. Here, we highlight four key areas that will benefit from an AI leader in your organization across every industry:
Increasing Operational Efficiency
AI can do many things for your organization. Perhaps the biggest of them is enact extraordinary levels of efficiency, cost savings, and faster decision-making. Take some examples:
- Process automation and workflow optimization using AI-powered tools like Robotic Process Automation (RPA) can automate repetitive, rule-based tasks, freeing up employees' time to focus on higher-value work and improving operational efficiency.
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AI algorithms can analyze large volumes of data at high speeds, uncover hidden patterns, trends, and insights to inform data-driven decisions and optimize operations.
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Complex supply chains built by global organizations that involve manufacturing processes and machines depend on large data repositories, comprised of enterprise resources such as SKUs, parts, employee data, availability and utilization of resources. Reviewing these and drawing insights by humans had required visualization tools in the past, but now AI can analyze in real-time and identify processes to be automated or improved.
Our take: Your Chief AI Officer has expertise in analyzing complex data sets and generating actionable insights, helping the company make decisions and identify newer opportunities. The tools he or she implements can help businesses forecast demand, identify potential issues, and optimize supply chain operations by analyzing historical data and identifying patterns.
Enhancing Risk Management
AI can create unparalleled, speedy protection when it comes to compliance and in identifying potential cyber-risks.
- Your company may have auditors within a finance function obsessing over how the company navigates potential ethical, legal, and security risks associated with business processes. In a similar way, Chief Information Security Officers (CISOs) implement controls to mitigate risks associated with treats to the company’s data and networks.
AI-powered systems bring the work to the next level. They are here to complement, and strengthen, the work of CISOs and auditors because these tools can monitor and analyze transactions, network activity, and user behavior in real-time, identifying potential threats and fraud attempts before they cause significant damage.
Our take: The AI leader will liaise with the leadership team to ensure risk mitigation solutions are implemented smoothly, integrated across the enterprise, and in compliance with industry and market regulations.
Accelerating Product Development
If AI was once viewed just as a productivity enabler, it’s now directly tied to product development cycle and business performance. For example:
- Companies are leaning on AI to develop unique products, services, and solutions to get ahead of competitors. Many have identified opportunities to deploy IIoT implementations across customer touch points. While previously the volume, velocity, and variation of such data could have overwhelmed traditional algorithms and ERP systems, AI tools have made machine-learning approaches practical and economical to implement.
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Chatbots deliver great customer experience and reduce the workload on customer service representatives. They collect behavioral information that leads to faster product development thanks to insights on market trends, customer needs, and potential improvements.
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What would your sales and marketing leader invest to create a more effective personalization and targeting engine that enables sales? AI can analyze customer data and preferences to provide personalized product recommendations, content, and marketing messages, increasing customer engagement and conversion rates.
Our take: AI leaders can help drive business innovation by identifying and exploring new applications, fostering a culture of experimentation and continuous learning that supports long-term growth.
Unlocking Growth Opportunities
- As traditional companies advance and become more tech-first, new challenges will arise. It is important for an AI leader to bring awareness of new trends, and be able to target possible acquisitions, at well-timed valuations from the startup world.
According to Paolo Guglielmini, President and CEO of Hexagon AB, this is particularly important given the challenge of generating customer value and operational effectiveness in the context of partnerships with the big tech players. “That’s reflected in the organization. Domain knowledge combined with an adequate mastery of tools and understanding of potential for AI technologies is king. And a much rarer skill to find than pure technical proficiency,” he says, adding: “A fundamental task for AI leaders will be to build that community, open and receptive to learning from peers and other industries, pragmatic in setting the pace and the goals of AI adoption."
Ultimately, successful outcomes will heavily rely upon how companies are using AI, which is also under this knowledge-sharing scope of the AI leader. As Justin Hotard, Executive Vice President & GM, HPC & AI Business Group and Hewlett Packard Labs, explains: “Enterprises that are betting on AI to deliver new sources of value recognize that responsible use of AI is foundational. Integrating across functions and business lines increases transparency in AI, making it safe and reliable to implement and generate meaningful outcomes.”
In the AI startup world, several emerging themes are shaping the landscape and driving innovation and potential growth for those corporations that could make synergistic acquisitions. There are plenty of such startups focused on AI-led innovation in a diversity of areas across Autonomous Systems, Healthcare, FinTech, Smart Infrastructure, Intelligent Edge computation, Cybersecurity, to the latest growth in the prominence of LLMs and Conversational AI.
From assisting in product development to providing companies with invaluable insights to achieve their objectives and beyond, AI can deliver a lot of value to companies. But they will need a capable leader at the forefront of their efforts. "One of the most profound impacts of AI is its transformative effect on human behavior and learning," says Gregory Bryant, President of Global Business Unit at Analog Devices (ADI), adding that has his company, technology is an enabler of positive outcomes. "At ADI, we play a crucial role in driving the digitization of the physical world, further generating exponential amounts of vital data for accelerating breakthroughs. With machines assisting in problem-solving, we can focus on strengthening our domain expertise and understanding of our customers' challenges, propelling innovation to new heights across industries like medicine, energy, and sustainability."
