• Super.com had its internal information scattered across several workspace platforms.
• The company built an artificial intelligence search tool to make a tool hub.
• This article is part of "Build IT: Connectivity," a series about tech powering better business.

The tools meant to streamline work can leave businesses stuck in a maze of messages, documents, and dashboards.

Super.com, a travel and finance platform on which customers can book hotels and earn cash and rewards, depends on various workspace platforms, including Slack, Confluence, and GitLab, to keep the business humming.

Hussein Fazal, Super.com's CEO, told Business Insider that juggling systems often slowed down day-to-day tasks. Documents, datasets, and message exchanges were scattered across platforms, which made it difficult for teams to access what they needed when they needed it.

During the COVID-19 pandemic, the company decided to permanently switch to remote work, which Fazal said added an extra challenge to information retrieval.

As a result, Super.com needed a central system to access information from all of its platforms.

"It's hard to just pick up information, and it can sometimes even be hard to get information," he said.

Super.com decided to build a hub that its employees could access from home. In 2022, the company teamed up with Glean, an AI startup in Palo Alto, California, to create a search platform that pulls information from across Super.com's software programs.

A personalized search tool

Enterprise search is software that allows users to look for information across various platforms and databases. Glean's platform uses ranking algorithms and generative artificial intelligence to make it easier for users to find what they're looking for.

"Glean will find the right information and produce an answer in natural language, à la ChatGPT, but with the information in the context of your enterprise," Tamar Yehoshua, the president of product and technology at Glean, told BI.

She said that it's not as straightforward as putting all the information together into one big pot. Different employees have different access permissions, so each search needs to be customized for whoever is using it.

Super.com integrated the company's most-used apps and tools, such as Slack, Confluence, GitLab, and Google Drive, into one hub. "It's personalized," she said. "It will find the information that is more relevant to you, as opposed to me, if we're in different roles and in different teams."

Yehoshua said the setup process could be challenging since some companies struggle with managing who has access to which tools. This means that the software could give out confidential information to employees.

To fix this, Glean built a data-governance layer into the search platform, which ensures rigorous access permissions. Fazal said Super.com had never had an issue with Glean's search tool giving people information they shouldn't be allowed to see.

Yehoshua added that while everybody knows how to search Google, not everyone knows how to write a good AI prompt. Glean also launched a prompt library for Super.com, which she said helped educate people on how to use the tool.

Fazal said he uses the platform multiple times a day. He added that an internal company survey found the search platform has saved employees an average of 20 minutes a day, which adds up to more than 1,500 hours saved each month across the team. The employee survey also found a 20% reduction in onboarding time for new hires.

Next steps for AI agents

Since their first partnership, in 2022, Super.com and Glean have added features to the platform. A generative-AI tool embedded into the platform, for example, helps employees draft emails and prioritize tasks using real-time company data.

For instance, if an employee asks, "What are the 10 most important things I should be working on right now?" the AI assistant will use information from Slack and Google Docs to give a customized answer to that employee.

Looking ahead, Fazal hopes to incorporate AI agents into the platform. He said the next step after prompting AI to generate a task list would be getting an AI agent to go do those things. For instance, the AI assistant might suggest arranging a meeting as an important task. The agent would then draft emails and book a meeting room to help complete that task.

"We're excited to test it out and implement that once it's ready," he said.

• By 2030, Deloitte predicted, 1 million skilled workers will be needed to power the semiconductor industry.
• Experts in the sector suggest looking to untapped talent pools and investing in training.
• This article is part of "How AI Is Changing Everything: Supply Chain," a series on innovations in logistics.

For years — since the first "Terminator" movie, really — employees have worried about artificial intelligence replacing them in the workplace.

Though AI implementation could lead to fewer jobs in certain industries, the power-semiconductor and data-center sectors — which manufacture and supply technologies like microchips, integrated circuits, and server farms — are bracing for a different reality: AI could create more jobs than it eliminates.

The reason is simple: demand. Since the semiconductor industry requires highly specialized labor and precision to build microchips and integrated circuits accurately, even the most powerful machines will require humans to ensure they're built and running properly.

As more technology companies embrace AI-powered technologies, the need for skilled engineers and technicians is expected to increase dramatically. In a recent report, Deloitte predicted that by 2030, more than 1 million additional skilled workers would be necessary to meet service demands in the semiconductor industry alone.

Industry experts told Business Insider that this would create opportunities for companies to hire a phalanx of talent focused on programming, quality assurance, and troubleshooting glitches.

Experts said it's also a reason for semiconductor companies to engage in upskilling, or the process of training employees to effectively use AI tools in their roles. This enables them to become more adaptable in the face of AI-driven workplace changes.

For companies to seize these hiring and upskilling opportunities, they must recognize the challenges associated with staffing for such a niche need, Larry Smith, a retired chair of the board of directors at Tokyo Electron, told BI.

Smith and John Akkara, the CEO of the IT staffing company Smoothstack, shared their top strategies for growing and preparing the data-center and semiconductor workforce to best leverage AI.

Cultivate the right skill sets

Even with AI and automation becoming more prevalent in semiconductor and data-center operations, humans are still important to their creation and functioning.

In a recent blog post, Michael Isberto of Colocation America, an on-demand IT infrastructure provider, wrote that humans have key roles in designing and maintaining data centers. And after one is built, technicians are needed to manage and troubleshoot the systems that store, process, and distribute sensitive data.

Smith has more than 35 years of experience in the microchip industry. He said it's important for companies to cultivate the right skill sets to assist with in-house needs like systems management and hardware repair.

"These are the tools of the future — especially when you're talking about AI," said Smith, who served as vice president, president, and chair of the board at Tokyo Electron over the course of 21 years. "Naturally, you want a group of humans who have the skills to rise to the occasion and execute."

Prepare to scale

Sometimes, a data center or semiconductor fabrication facility may need to double or triple its capacity in a matter of weeks. This means that the machines running AI systems need to work faster, longer, and harder and that companies must be ready to scale their human workforces to service these machines.

One organization that enables quick scaling is Uptime Crew, a new subsidiary of Smoothstack.

The company makes talent training plans customized for its clients' needs, Akkara said. The plans are typically designed to get workers hired, trained, and deployed to a job for one of its clients within 10 to 12 weeks.

"The whole idea is that our teams mobilize quickly," Akkara said. "Especially with AI, in the current climate, you need to move fast and be able to work with all the technologies on the market."

The company is nascent and just getting its system off the ground, but it plans to work like this: A semiconductor company wants to expand its AI operations, then goes to Uptime Crew to find and hire specifically skilled workers, like data-center technicians, to get the job done. On the first day of the job, these workers would arrive trained and ready to go.

Consider untapped talent pools

Smith said that with upskilling, companies may find some of the best employees for particular jobs among the retired.

Take the microchip industry. Smith said that the vast majority of semiconductor and robotics operations are run by people who previously worked as military equipment maintenance or field technicians.

Here, the upskilling was seamless: Thanks to their experience troubleshooting problems, crunching codes, and monitoring systems, the former maintenance and field techs were able to step into their new jobs without training delays.

Smith said that he'd love to see military veterans get some of the new and forthcoming AI-focused data-center jobs since these roles require workers with years of experience and highly specialized skill sets, like engineering and quality control.

"The semiconductor industry is important for national security, and those are the kinds of jobs that veterans look for," Smith said. "It seems like too good of a fit not to investigate at the very least."

The staffing company Salute Mission Critical, for example, specializes in staffing and servicing data centers and was cofounded by the veteran Lee Kirby. During a recent podcast interview, Kirby said that the company was established in part to help veterans develop careers in the data-center sector.

Invest in training

Considering the specialized nature of data-center and semiconductor jobs, investing in training is another important factor for companies to think about.

Case in point: Microsoft. This year alone, the company plans to spend $80 billion to build out AI-enabled data centers, Microsoft's vice chair and president, Brad Smith, wrote in a January blog post. At a March event, Smith said Microsoft would pay for 50,000 workers' technical certification exams — for skills related to cloud architecture, AI, and cybersecurity — as part of a training initiative for its South Africa data centers.

Akkara said that when company leaders invest in AI training, they're also investing in the future of the company and its workers.

"You're giving them specialized skills, but you're also giving them new skills that will be valuable today and down the road," Akkara said. "As AI becomes more pervasive, the need for these particular skills is only going to increase."

He added that Uptime Crew constantly evaluates workers' skills through performance reviews and supervisor observation so temporary employees stay motivated to finish their jobs. He said that if certain staffers don't work well for its clients, Uptime Crew replaces them.

In scenarios like this, Uptime Crew clients will also use the service to hire for existing open roles and educate themselves about anticipated skill set needs so that they can strategize for hiring accordingly.

"Technology needs are always changing," Akkara said. "Companies need to be ready for anything."