For businesses, decisions about investing in AI are complex and challenging.
Artificial Intelligence (AI) is reshaping business operations, from network troubleshooting and cybersecurity to customer service and communications. As investment in AI reaches new heights, organizations must weigh its benefits against cost, environmental impact, ethical concerns, and implementation challenges.
The global system integrator World Wide Technology (WWT) recently hosted a tech talk with leaders from Cisco, Intel, and NetApp to discuss key considerations for adopting AI in business. They examined various AI investment options and outlined an effective AI investment strategy. This included ways to address the skills gap in AI, and tactics for incorporating security and sustainability into an AI strategy. Here are the key takeaways from that discussion.
Transforming Operations & Enhancing Security/Privacy With AI Investment
The impact of artificial intelligence on operational efficiency and security is significant, and its applications are diverse. Cisco leverages AI in security through predictive analytics and pattern recognition. This application of AI allows Cisco to identify potential cyber threats before they can cause harm proactively. By analyzing data patterns and detecting anomalies, Cisco’s AI-driven security approach enables faster response times and improved threat mitigation in networking.
NetApp focuses on AI’s ethical use and deployment to enhance security, particularly in protecting intellectual property (IP) and sensitive data. The company prohibits using public generative AI services within the internal network, having developed its own secure version. This ensures NetApp data, as well as that of its clients, remains protected.
“Looking at Twitter, Facebook, and Instagram, I fear that AI can be weaponized,” said Paras Kikani, senior director of solutions engineering at NetApp. “So, we have to be responsible and ensure that we’re not only implementing AI the right way but also protecting ourselves simultaneously. The IP that you all hold just can’t go into the public domain.”
Intel works with partners to develop large domain-specific language models tailored to specific industries like finance, healthcare, and manufacturing. The goal is to make AI intuitive and practical, focusing on real-world problems and areas where customers genuinely need solutions.
For example, Boston Consulting Group (BCG) and Intel have teamed up to create an AI model trained on BCG’s confidential data, spanning over 50 years. BCG employees can now retrieve and summarize information that was previously difficult to find using a chatbot powered by Intel AI hardware and software while keeping the data private.
Cisco is also cautious, advising against the use of public generative AI services. For instance, Cisco has its own internal AI platform leveraging Microsoft’s Azure AI capabilities. This reflects a broader trend Cisco observed among its customers. Financial services firms tend to be wary of AI, whereas manufacturing companies are more open to it. Cisco believes providing employees with viable, secure alternatives to public AI tools is essential.
“You can’t say no,” said Eric Knipp, Cisco’s vice president of systems engineering, Americas. “Just like with security, they will find ways around it if you make it hard. Versus giving them a tool that they can work with, backed up by your own internal policies.”
Sustainability & Cost Considerations for Deploying AI
Industry leaders are deeply aware of the sustainability challenges, notably the high energy consumption associated with generative AI. It requires extensive floor space and cooling in an era where there is a trend toward reducing power usage and creating smaller, hybrid environments.
Organizations risk being overly enthusiastic about AI investment, leading them to adopt it without fully understanding its purpose or impact on the environment. An AI investment strategy must therefore consider sustainability and cost-efficiency.
“GenAI is not exactly a green technology. A ChatGPT search takes about 100 times more power than a typical Google search. As we think about driving these types of solutions into our customers’ environments or into our enterprise environments, we need to be cognizant of the potential impact that’s going to make,” said Knipp.
AI implementation is costly due to the need for high-end graphics processing units (GPUs), high-performance storage, and extensive datasets. Balancing these expenses puts more strain on already tight IT budgets. According to Kikani, AI must prove its value in “helping the core business” by generating revenue, fueling growth, reducing risk, cutting costs, or optimizing resource use. It’s important to thoroughly understand AI, including its intended purpose and how to use it most efficiently, effectively, responsibly, and securely.
“Everybody is so enamored with AI that we’re getting ahead of ourselves without really understanding what AI is. It’s a tool. It’s a hammer, it’s a nail. It’s not going to replace everything,” said Travis Palena, Intel’s global channel sales director for data center and AI.
Future Workforce: Bridging the Skills Gap
People who have spent years in specific roles must now adapt to new demands and technologies, as evidenced by the recent layoffs at major tech companies. Cisco, Intel, and NetApp acknowledge an industry-wide need for apprenticeship programs, internships, and educational initiatives to help foster the next generation of tech-savvy professionals.
NetApp, for example, has a program called Sales, Support and Services (S3) Academy, which provides training to recent college graduates and those with a few years of experience. However, NetApp also recognizes the importance of continuous learning for midcareer professionals to succeed in today’s fast-paced tech world.
“As our corporate responsibility, we need to build programs to not only help our early career individuals but also people who have been in industry for five to 10 years and haven’t had a chance to learn something new,” said Kikani.
Cisco is approaching the skills gap by leveraging its existing Network Academy program to recruit people who may not have a four-year degree but can learn relevant tech skills. This initiative reflects a broader perspective on talent acquisition and the value of looking beyond conventional four-year degree holders. The Department of Defense’s SkillBridge is an example of a program that helps veterans transition to corporate jobs. Cisco has recruited more than 120 veterans through this program so far.
Bottom Line: AI Investment
The decisions about investing in AI are complex and challenging. But by focusing on early-career individuals, nontraditional talent pools, and veterans, organizations have the opportunity to broaden their recruitment strategies and invest in the current workforce to meet the challenges of rapidly evolving technologies like AI.
