Key Takeaways
- AI as a Core Skill: AI fluency is now a baseline business skill across analytics, marketing, finance and operations.
- Role-Specific Tools: The most valuable AI tools depend on the role students are preparing for, including research, data analysis, presentations, automation and customer insights.
- Skills That Matter: Strong prompting, verification and documentation skills matter as much as the tools themselves.
- Responsible Use: Responsible use is essential to protect data and credibility.
- Job-Ready Focus: This guide focuses on practical, job-ready workflows.
Artificial intelligence has ushered in the age of automation and augmentation in the business world. Businesses are looking for ways to ensure their employees are working on only the most important projects, leaving the boring, menial tasks to be handled by AI tools.
Despite that desire, AI hasn’t yet proven to be effective in that space. According to Deloitte’s 2026 State of AI report, 84% of companies have not redesigned jobs around AI capabilities.
That means that humans remain a crucial part of the equation still, providing valuable and not yet replaced work. And these AI tools are crucial for business students.
AI used for augmentation
In fact, AI tools can help humans do better, more complete work. It can help them dial in a presentation, generate content ideas for a new campaign or create a mock app for a new product launch.
In many cases, the Daniels College of Business encourages students to experiment with AI tools, as they’ll be expected to know how to use them when they graduate. There is a balance to be struck, as students are still expected to produce original work and disclose any AI usage. Policies vary by course and professor, and students should consult the syllabus before using any tools on classroom assignments.
Experts at Daniels
Michael Myers
Michael Myers, teaching professor in the Department of Marketing, encourages his students to stay on the cutting edge of AI. He frequently brings new applications into his classes, helping students learn how to apply them to a business case.
Nick Machol (BAcc 2008, MAcc 2008) shares Myers’ affinity for artificial intelligence, so much so that he started a business around it, Unburdn. His team helps companies implement AI into their businesses, helping them find efficiencies by making the technology understandable and accessible.
While the landscape is changing rapidly, the two experts shared their favorite AI tools every business student should master.
1.) Research and summarization tools
Whether you’re doing competitor research, industry scans or searching information to fill a briefing memo, research and summarizations tools can serve as a helpful starting place. Myers and Machol like tools like Claude, ChatGPT, Gemini and Perplexity here. Machol’s latest preference is Claude, adding, “This is my daily driver. I use it for research, writing, analysis and brainstorming.”
He also recommends NotebookLM as a strong tool where you can upload papers, articles, podcasts or YouTube videos to build an interactive knowledge base. From there, you can limit a query to that specific information.
“The audio overview feature is incredible for synthesizing complex material and learning how to articulate it to others,” Machol said.
2.) Writing and editing tools
Many of the same tools can help with writing and editing. Try out Claude, ChatGPT or any of your preferred generative AI chatbots as an early resource. There’s also Grammarly and Machol’s preference of Wispr Flow, an AI-powered voice-to-text application that he says “works the way you wish Siri worked.”
“I call it the ‘post-keyboard life,’” he said. “Students are writing thousands of words a week. This lets you think out loud and rip through work dramatically faster.”
Nick Machol
One word of caution: These tools shouldn’t replace original writing and careful human edits. You still have a crucial role to play in ensuring these works match your thought process and strike your writing tone.
3.) Data analysis and visualization tools
When it comes to AI data analysis and visualization tools, Machol touted the value of integrating Claude into Excel.
“It’s unreal. It’s like having a junior analyst on your desktop,” he said.
There’s also Tableau, Power BI and Hex as options.
4.) Presentation and storytelling tools
Both Machol and Myers like Gamma for presentations, as it helps provide an AI guide to presentations. Feed it data, documents and more to help craft the baseline for a presentation.
Canva has integrated AI tools, making graphic design elements easier to create. These tools provide a strong starting point for presentations, but require human analysis to ensure they aren’t generic.
5.) Automation and productivity tools
ChatGPT, Claude and Copilot all offer integrations into meeting software and email systems, making them a natural fit for automation and productivity.
Machol likes Granola as well, as it serves as an AI note taker that he says “works the way your brain wants it to.”
“It captures meeting and class transcripts, then lets you build a searchable second brain around everything you’ve heard. For students sitting in lectures and group projects, this is a game changer,” he added.
The AI skills that make tools actually useful
These AI tools can be helpful, but they do require some expertise to use them. There are certain skills that can help you get more quickly up to speed and use the tools to their maximum potential.
Prompting for business outcomes
Prompting is often the first step, as it ensures the AI output truly matches what you’re looking for and arrives in the format you need it.
A common prompt pattern could look like this:
- Define the AI agent’s role
- Give it your end goal, describing the constraints you’re working under
- Provide a rubric for it to work off
- Lay out the preferred format
With that level of detail, your output is likely to approach the deliverable that you envisioned before you prompted your AI tool.
And even if it still falls short, it’s important to draft, critique and revise your outputs. This iterative process is crucial to getting to a desirable end product.
Verification and source hygiene
Regardless of how much diligence you have during the prompting process, you should still fact check your AI deliverable. Research its claims and numbers, investigate its citations and ask it to show its work. While AI is powerful, it isn’t infallible.
Data privacy and professionalism
Given AI’s relative infancy, publicly available AI tools also rely heavily on user interactions for training and operations. This means that your data is being used to refine and train AI algorithms. With that in mind, don’t paste private information, like client data or student records, into AI tools.
Frequently Asked Questions
What AI tools should business students learn first?
The most valuable AI tools depend on the role students are preparing for, including research, data analysis, presentations, automation and customer insights. The goal is building AI fluency across these areas.
Can AI tools be used for class projects and case competitions?
AI can support practical, job-ready workflows like research, data analysis and presentations, but students should ensure their work stands up to real-world scrutiny and reflects their own thinking.
How can students verify AI-generated insights?
Strong prompting, verification and documentation skills matter as much as the tools themselves. Students should evaluate outputs and ensure their work stands up to real-world scrutiny.
What information should never be entered into AI tools?
Responsible use is essential to protect data and credibility. Students should avoid entering sensitive information that could compromise either.
How can students turn AI skills into career advantages?
AI fluency is now a baseline business skill across analytics, marketing, finance and operations. Students who can apply practical, job-ready workflows and evaluate outputs will be better prepared for real-world roles.