Cio Rom Kosla's summary of the importance of emerging technologies for Hewlett Packard Enterprise (HPE) probably resonates with senior management. “AI is in our hearts.”
Research suggests that Kosura is not alone. A recent McKinsey survey found that three-quarters of business leaders (78%) report that their organizations use AI in at least one business function.
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Kosla told ZDNET that HPE used a third-party application with built-in AI capabilities and spent the last 18 months developing an internal chat solution called Chathpe, a generated AI hub used for internal processes.
Below are four ways to use Kosla's experience to transform AI into business benefits.
1. Establish an AI strategy
Like other Blue-chip enterprises, HPE uses multiple external AI models and technology platforms. Experts use Microsoft Copilot to increase productivity, while developers use GitHub Copilot.
“The goal here is to use these technologies to help them do their day to day work when we deploy licensing to individuals,” Kosra said.
This strategy will be more interesting, centering on Chathpe, a bespoke platform powered by Azure and Openai technology.
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Kosla said the company has a pipeline of rated and evaluated use cases. For example, legal teams may want to use AI to review contracts, extract specific insights, and generate new templates.
“Then what we're doing is working with them, leveraging Chathpe and pointing to specific source data,” Kosla says. “We also restrict access to data because people don't want to use information without attention or consideration.”
He also outlined how use cases can bubbly in other areas of the business.
“In operation, it's around the chat. You can think of it as something for customer service. For example, there may be a use case where people want to find a part number.
He added that marketing can identify which campaigns can be reused using Chathpe, and that finance can select a use case for the analytics.
2. Train everyone to use AI
Kosla said his staff often discusses majors and minors' concepts in their journey to becoming a mature IT organization.
“If you're thinking about university, maybe you're focusing on economics, and that's what you really want to do,” he said. “However, it's not harmful to master financial, marketing or computer science minors. All of these create a healthy view of the opportunities that you can apply.”
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According to Kosla, that is the approach HPE takes on AI. The company hopes that all employees will look at various majors and minors as areas of skill and make them competent.
“If your major is in the supply chain, you have to be a minor in AI. Or if your major is in AI, you have to be a minor in the supply chain,” he said. “Everything we are trying to cross the boundaries of other areas of business, so you need to be as diverse as possible in your knowledge.”
Kosla explained how HPE's major and minor concepts are enhanced by AI-focused learning and development. “We enable training in the HR system. People can come in and learn. The goal here is to make AI training available to everyone,” he said.
However, this focus does not stop at training. Kosra emphasizes how important the following-through after facts are. “Because they employ technology, my rule is always saying, 'If you learn it, you need to use it', it's not great to have a certificate and not be able to apply knowledge. ”
3. Place the guardrail in place
Kosla said it is already clear that AI will permeate all organizations, functions and roles and have a reasonable impact on information access. Smart business leaders focus on managing agent technology and its relationships with human counterparts.
“From an IT perspective, I'm thinking about control and guardrails,” he said. “You need human factors to understand the question of what the machine is doing and what decisions they are making on your behalf. How do you ensure that those guardrails are fine-tuned, tightened or expanded, depending on the scale of what you are trying to do?”
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Kosra said these guardrails are only established and refined by effectively partnering with the business.
“The first thing to do is to say, “How can I see how to properly manage fast engineering, have limited data extracted, ensure that the amount of training is properly managed and the answers from the engine are accurate?”
He continued: “There are important phrases that you don't want to respond to the engine because potentially the answer can be dangerous or harmful. So what we're trying to do is to ensure that the prompt is for business use.
4. Think about where you're going next
Kosla said HPE's internal approach to AI continues to mature, with the company mixing internal and external models according to its requirements. The company's current focus is to use AI to enhance operational activities of its staff.
However, Kosra also realized that AI agents are evolving quickly. His company already uses software from other providers that implement agent services, such as SAP and Salesforce.
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One of the key questions HPE is considering is AI orchestration across the end-to-end behavioral model.
“If you coordinate between two providers, have two different agents, but the individual is using both and pivoting the chair between one application and another, they may find themselves not talking to each other,” he said. “So we need to build that orchestration layer, or we have to find best practices on the issue.”
Kosra said these technical issues will soften some of the hype around agents.
“When you think about individuals, they're not tied to one application,” he said. “That's the challenge we face. There's a lot of sales when it comes to agents. But you're not an agent doing finance. And the funds, quotes, pricing, and all of those systems interact together.”
