Gen AI Q&A
10 Things IT and the C-Suite Need to Know
Written by Rachel Howard
ContributorsAmol Ajgaonkar, Meagan Gentry,Rob Green, Joyce Mullen, Matt Skaff, Carmen Taglienti
With its remarkable ability to generate content, enhance human creativity and execute time-consuming tasks in mere seconds, the possibilities for AI’s practical applications are endless. And yet, wide-scale adoption is sputtering along.
Let’s consider the mainstream birthdate of generative AI as the ChatGPT launch craze in late 2022. That means the revolutionary tech is now in its second year of wide-scale availability — and experimentation.
If your initial experiences with generative AI fell flat, we’re here to tell you keep using it. The reason is simple. “What really strikes me about generative AI is that right now is the worst version it’s ever going to be. It’s going to keep being iterated on and made to be more powerful,” says Megan Amdahl, senior vice president of client experiences and chief operating officer of Insight North America. Amdahl is tightly in tune with the competitive landscape of Insight clients and to the upcoming technology advancements from software and device manufacturers. She’ll be the first to tell you: if you want to be a competitor in the future, AI needs to be your status quo today.
Likely, you already know this. Perhaps, like many others, adopting generative AI is no longer a question of “why” but “how.” So we’ve collected the most commonly asked questions we hear from clients trying to get ahead with this transformative technology. Read on as we’ve tapped our technical and strategic leaders for the answers.
IT leaders have three methods of deploying generative AI: (1) create a new AI model from scratch (uncommon); (2) adapt an existing model to fit specific needs or (3) use a pre-built model (very common).
While creating a custom AI model requires a higher cost and time investment, it can provide a competitive advantage for organizations with unique data and business functions. But it’s very rare that you’d need to train your own model.
Adapting existing AI models is the most common use case. Another company’s data scientists and AI architects have already created a model for their general use cases. But, this is where other organizations can fine-tune the model to understand more about their specific data and operations.
— Meagan GentryNational AI Practice Manager, Insight
While gen AI is poised to enhance productivity and drive innovation, it can also be destructive in the wrong hands. Hackers can leverage the technology to perpetrate attacks on essential infrastructure, facilitate data breaches and even turn proprietary models against their owners.
Organizations are looking to apply AI to remediate cybersecurity issues and protect from future threats. But malicious players are just as rigorously working to use it against us, including the creation of more sophisticated phishing emails. Advancements in AI will lead to more complex, targeted attacks, but implementing Zero Trust and principles of least privilege can protect against any type of attack, whether AI-generated or not.
— Carmen TaglientiChief Data Officer and Distinguished Technologist, Insight
The growth of generative AI is having a significant impact on device requirements and refresh lifecycles. Traditional devices may not have the processing power necessary to handle the demands of generative AI and more complex, intelligent operations, which can result in slower performance and decreased efficiency. By investing in next-gen, on-device AI, you’re getting faster processing and a more efficient use of resources. And many organizations are at an ideal point in their device lifecycle to make that investment.
— Matt SkaffVP of IT, Insight
Learn more about generational AI perceptions in the full report: Insight Intelligent Technology™ Report: Quantifying Employee Attitudes Toward AI-Powered Devices
The implementation of AI-powered devices in the workplace has led to a mix of emotions among different generations of employees, but overall, there is a positive outlook on AI’s potential to improve daily work life. Based on a March 2024 survey by Insight and The Harris Poll, 75% of employees believe that AI-powered devices will help their employer stay competitive. What’s more, 73% expect AI devices to improve their own productivity. Generally, Boomers/Gen X are cautious, Millennials are hopeful and Gen Z is curious about the future of AI in the workplace.
The first step in being smart about AI is for companies to identify all potential use cases and prioritize them based on their value and feasibility. This involves asking questions such as “What are all the things we wish we could do?” and working with partners or AI engineers to determine what is feasible based on the data available and the business integration required.
The use cases should be ordered and prioritized based on their value and level of complexity, with a focus on the highest ROI use case that is most feasible today. This may require assessing the maturity of the data state and identifying applications that would benefit from AI integration.
At Insight, we’re committed to empowering our employees to use generative AI effectively in their day-to-day work. To achieve this, we are enabling training opportunities that focus on prompt engineering. By designing questions that are tailored to the specific needs of the user, we can elicit the best possible response from the AI system. We recommend starting with specific prompts that are tailored to a specific persona. (That is, a prompt for a developer will differ from that of a marketer.) It’s also worth noting that AI systems may sometimes produce fabricated information, or hallucination. To avoid this issue, we suggest asking the AI to cite its sources or provide supporting information. By doing so, you can verify the sources to ensure the technology is providing accurate responses.
I’ll lean into sort of the technology shifts that we’ve seen over the last 20, 30 years — because fear of job loss is a very common theme that emerges. There’s that anxiety that this is going to be disruptive. Typically, what happens is the new technology creates new roles and displaces some legacy roles. With generative AI, I think the legacy roles that are going to get displaced are those that are pretty rote. Roles that gen AI can really lean into and automate. And so, if you’re in a role like that, you might want to think about retooling, reskilling and leaning into the capabilities of gen AI so that you remain relevant or become more relevant as we go forward. But I think we’re also going to see new roles created.
— Rob GreenChief Digital Officer, Insight
Generative AI offers a spectrum of capabilities that are creating a competitive advantage for organizations across various domains. One prominent area is content creation, where generative models can produce high-quality text and images, enabling businesses to streamline content generation processes, personalize customer interactions and enhance marketing campaigns with greater agility. An example might be using the technology to develop product descriptions and expedite e-commerce operations. Similarly, AI-generated art or design assets can provide inspiration for creative direction and execution, allowing for collateral to be produced (and go to market) faster.
Generative AI empowers organizations to rethink and reengineer their business processes, aligning them more closely with desired outcomes such as enhanced customer experience and risk reduction. Through the synthesis of Large Language Models (LLMs) and the development of personalized models tailored to enterprise data, businesses can unlock new insights and opportunities for innovation.
By embracing generative AI technologies and investing in customer education and training, organizations can unlock the full potential of these tools, driving continuous improvement and sustainable growth in today’s competitive landscape.
— Joyce MullenPresident and CEO, Insight
Watch the video for an in-depth look at the generative AI sales solution.
At Insight, we’re using generative AI in a lot of ways across the organization. One example is a gen AI solution we developed for sales to streamline the process of generating statements of work for customers. The solution involves answering a few questions about the customer’s challenges, considerations, duration and other preferences, and hitting “generate” to receive a complete statement of work. This includes details on deliverables, duration and legal assumptions, among other things. The solution also includes a risk analysis phase, which flags any changes made to the assumptions and allows for review before approval. The entire process takes just 30 seconds to generate the scope of work and another 30 seconds for approval and risk analysis, cutting out a lot of tedious work for Insight’s sales team.
— Amol AjgaonkarCTO of Product Innovation, Insight
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