According to a June 2025 PYMNTS Intelligence report, “The Agentic Trust Gap: Enterprise CFOs Push Pause on Agentic AI,” all the CFOs surveyed said generative AI has increased the need for more analytically skilled workers. That’s up from 60% in March 2024.

“The shift in the past year reflects growing hands-on use and a rising urgency to close capability gaps,” according to the report.

The CFOs also said the overall mix of skills required across the business has changed. They need people who have AI-ready skills: “CFOs increasingly need talent that can evaluate, interpret and act on machine-generated output,” the report said.

The CFO role itself is changing. According to The CFO, 27% of job listings for chief financial officers now call for AI expertise.

Notably, the upskill challenge is not limited to IT. The need for upskilling in AI affects all departments, including finance, operations and compliance. By taking a proactive approach to skill development, CFOs can position their teams to work alongside AI rather than compete with it.

The goal is to cultivate professionals who can critically assess AI output, manage risks, and use the tools to generate business value.

Among CEOs, the impact is just as pronounced. According to a Cisco study, 74% fear that gaps in knowledge will hinder decisions in the boardroom and 58% fear it will stifle growth.

Moreover, 73% of CEOs fear losing ground to rivals because of IT knowledge or infrastructure gaps. One of the barriers holding back CEOs are skills shortages.

Their game plan: investing in knowledge and skills, upgrading infrastructure and enhancing security.

Here are some ways companies can upskill their workforce for AI:

Ensure Buy-in by the C-Suite

• With leadership from the top, AI learning initiatives will be prioritized instead of falling by the wayside.
• Allay any employee concerns about artificial intelligence replacing them so they will embrace the use and management of AI.

Build AI Literacy Across the Company

• Invest in AI training programs: Offer structured training tailored to finance to help staff understand both the capabilities and limitations of AI models, according to CFO.university.
• Promote AI fluency: Focus on both technical skills, such as how to use AI tools, and conceptual fluency of AI, such as understanding where AI can add value and its ethical implications, according to the CFO’s AI Survival Guide.
• Create AI champions: Identify and develop ‘AI champions’ within the team who can bridge the gap between finance and technology, driving adoption and supporting peers, according to Upflow.

Integrate AI Into Everyday Workflows

• Start with small, focused projects such as expense management to demonstrate value and build confidence.
• Foster a culture where staff can explore AI tools, automate repetitive tasks, and share learnings openly.

Encourage Continuous Learning

Make learning about AI a continuous process, not a one-time event. Encourage staff to stay updated on AI trends and tools relevant to finance.

• Promote collaboration between finance, IT, and other departments to maximize AI’s impact and share best practices.

Tap External Resources

• Partner with universities and providers: Tap into external courses, certifications, and workshops to supplement internal training.
• Consider tapping free or low-cost resources, such as online courses and AI literacy programs offered by tech companies (such as Grow with Google). These tools can provide foundational understanding and help employees build confidence in using AI responsibly.

Read more:

CFOs Move AI From Science Experiment to Strategic Line Item

3 Ways AI Shifts Accounts Receivable From Lagging to Leading Indicator

From Nice-to-Have to Nonnegotiable: How AI Is Redefining the Office of the CFO

The Velvet Sundown, a four-person band, or so it seems, has garnered a lot of attention on Spotify. It started posting music on the platform in early June and has since released two full albums with a few more singles and another album coming soon. Naturally, listeners started to accuse the band of being an AI-generated project, which as it now turns out, is true.

The band or music project called The Velvet Sundown has over a million monthly listeners on Spotify. That’s an impressive debut considering their first album called “Floating on Echoes” hit the music streaming platform on June 4. Then, on June 19, their second album called “Dust and Silence” was added to the library. Next week, July 14, will mark the release of the third album called “Paper Sun Rebellion.” Since their debut, listeners have accused the band of being an AI-generated project and now, the owners of the project have updated the Spotify bio and called it a “synthetic music project guided by human creative direction, and composed, voiced, and visualized with the support of artificial intelligence.”

It goes on to state that this project challenges the boundaries of “authorship, identity, and the future of music itself in the age of AI.” The owners claim that the characters, stories, music, voices, and lyrics are “original creations generated with the assistance of artificial intelligence tools,” but it is unclear to what extent AI was involved in the development process.

The band art shows four individuals suggesting they are owners of the project, but the images are likely AI-generated as well. Interestingly, Andrew Frelon (pseudonym) claimed to be the owner of the AI band initially, but then confirmed that was untrue and that he pretended to run their Twitter because he wanted to insert an “extra layer of weird into this story,” of this AI band.

As it stands now, The Velvet Sundown’s music is available on Spotify with the new album releasing next week. Now, whether this unveiling causes a spike or a decline in monthly listeners, remains to be seen. 

I have always been passionate about gaming and technology, which drove me towards pursuing a career in the tech writing industry. I have spent over 7 years in the tech space and about a decade in content writing. I hope to continue to use this passion and generate informative, entertaining, and accurate content for readers.

But how are AI agents different from AI chatbots, and why should businesses care?

Understanding how they differ can help businesses choose the right solution for the right job and avoid underusing or overcomplicating their AI investments.

An AI chatbot or assistant is a program that uses natural language processing to interact with users in a conversational way. Think of ChatGPT. It can answer questions, guide users and simulate dialogue.

Chatbots only react to prompts. They don’t act on their own or carry out multistep goals. They are helpful and conversational but ultimately limited to what they’re asked.

An AI agent goes a step further. Like a chatbot, it can understand natural language and interact conversationally. But it also has autonomy and can complete tasks. It is proactive.

Instead of just replying, an AI agent can make decisions, take actions across systems, plan and carry out multistep processes, and learn from past interactions or external data.

For example, imagine a travel platform. An AI chatbot might help a user plan their travel itinerary. An AI agent, on the other hand, could do more, such as:

• Understand the request, such as booking a flight to Los Angeles.
• Search multiple airline sites.
• Compare flight options based on user preferences.
• Book the flight.
• Send a confirmation email.

All of this could happen without the user needing to click through a series of links or speak to a human agent. AI agents can be embedded in customer service, HR systems, sales platforms and the like.

Read also: Understanding the Difference Between AI Training and Inference

Why Businesses Should Care

Knowing the difference can help a business plan more strategically. AI chatbots use less inference than AI agents and therefore are more cost-effective. Moreover, businesses can use AI chatbots and AI agents for very different outcomes.

AI chatbot use cases include the following:

• Customer service
• Data retrieval
• Planning and analysis
• Basic IT support
• Conversation
• Writing documents
• Code generation

AI agent use cases include the following:

• Automated checkout
• Automated content curation
• Travel and reservation execution tasks
• Shopping and payment processing

AI chatbots and AI agents both use natural language and large language models, but their functions are different. Chatbots are answer machines while agents are action bots.

For businesses looking to improve how they serve customers, streamline operations or support employees, AI agents offer a new level of power and flexibility. Knowing when and how to use each tool can help companies make smarter AI investments.

To choose between deploying an AI chatbot or AI agent, consider the following:

• Budgets: AI chatbots are cheaper to run since they use less inference.
• Complexity of use case: For straightforward tasks, use a chatbot. For tasks that need multistep coordination, use an AI agent.
• Skilled talent: Assess the IT team’s ability to handle chatbots versus agents. Chatbots are easier to deploy and update. AI agents require more advanced machine learning, natural language processing and other skills.

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