As artificial intelligence (AI) matures, it’s moving beyond high-level experimentation and into hands-on roles within organizations. AI agents—automated tools that take on specific tasks—are poised to become essential, not for flashy purposes, but for performing practical work that drives efficiency across industries.
A new report from the Wharton School of Business of more than 800 senior business leaders found that weekly usage of Gen AI nearly doubled in the last year from 37% in 2023 to 72% in 2024. With the rise of AI agents that grant near superhuman levels of productivity, 2025 will be the year AI shifts from a novelty to a necessity by automating routine yet essential tasks.
Setting Realistic Expectations for AI Progress
While large language models (LLMs) have dominated AI news, there’s now an emerging realism about their limitations. Most recently, OpenAI signaled that their flagship GPT model was seeing lower rates of improvement, leading to questions within the industry of what the next phase of development will look like. But while the industry and researchers forge new paths, it’s important to acknowledge that just like any tool, LLMs drive the most impact when applied to a specific use-case and are no silver-bullet.
In some cases, we’re seeing a mixed-tech approach, where organizations leverage a combination of technologies like deep learning, ML models, and expert systems alongside LLMs to address different needs. This strategic use of technology is not only more efficient but more aligned with practical problem-solving.
Companies are also becoming more discerning about which technology to use, prioritizing reliable, smaller models for quick, efficient tasks and saving large models for complex problem-solving. This blending of technology creates flexible solutions that combine cutting-edge AI with traditional methods, enhancing productivity without overcomplicating the workflow.
Leveraging AI Agents for “Boring” But Essential Tasks
Some of the most impactful uses of AI agents are also the least glamorous. Contrary to the “moonshot” mentality, many organizations are discovering the power of deploying AI agents for seemingly mundane tasks that make a significant difference in efficiency. As research on AI in scientific discovery shows, AI can streamline idea generation and other repetitive steps, allowing high-judgment tasks to remain in human hands. By tackling these overlooked applications, organizations can make real gains in efficiency while freeing human talent for strategic work.
Take contracts, for example. A recent survey from LegalOn Technologies found that the average legal professional spends 3 hours or more reviewing a single contract. By using LLms to automate contract reviews, legal professionals can dramatically increase their capacity while freeing them up to do more impactful work. This increased capacity and efficiency doesn’t have to result in labor displacement, either. Instead, reassigning staff to other higher-value areas of the organization can result in improved productivity and enhanced customer service.
With AI agents that enable large language models (LLMs) to take action, the potential to reshape business operations reaches new heights. These agents go beyond handling routine tasks; they facilitate smoother collaboration by acting as active partners in daily processes. From scanning unstructured documents to managing customer inquiries, AI agents provide scalable solutions that evolve alongside an organization’s growth and changing needs.
Examples like these showcase how AI agents can subtly transform essential operations, freeing teams from repetitive tasks to focus on more strategic goals. By targeting these often-overlooked areas, organizations not only improve efficiency but also enhance customer experience and responsiveness. These “behind-the-scenes” applications may not be flashy, but they reveal AI’s real power to help businesses adapt, scale, and meet higher expectations—all without the need for high-profile, resource-intensive initiatives.
Practical Applications and Industry Impact
With AI tools becoming more accessible to organizations of all sizes, industries are beginning to see the benefits of specialized AI agents that tackle specific tasks in targeted ways. This broader access to AI means that even smaller companies, without extensive technical resources, can leverage powerful AI solutions for practical challenges.
Here are a few areas where AI agents are making a difference:
- Conversational Interfaces and Document Analysis: Sectors like customer service and legal are utilizing AI-powered chat agents to automate client inquiries and analyze unstructured data from transcripts, audio recordings, and more. The impact is twofold: businesses can serve customers faster, and employees are freed from repetitive tasks.
- Code Review and Security Monitoring: In tech-driven industries, AI agents support software development by continuously reviewing code and scanning for potential vulnerabilities, providing real-time alerts to prevent issues before they escalate and flagging best practices to streamline efficiency.
- Healthcare and Financial Services: AI agents are assisting in areas such as document processing, regulatory compliance, and risk assessment—offering time savings and enhanced accuracy, particularly valuable in highly regulated industries.
By focusing on practical applications, AI agents are unlocking new possibilities, making complex tasks like unstructured data processing and compliance monitoring more accessible and manageable.
Embracing Practical AI in 2025: Democratizing Access and Empowering Teams
As AI moves into the hands of more teams, a democratized approach is making powerful, real-time AI accessible to organizations of all sizes. Localized AI agents provide a bridge between theoretical capabilities and actionable results, allowing businesses to experiment, test, and deploy AI without heavy reliance on cloud infrastructures. This shift to local, device-based AI supports both security and data privacy, giving companies more control over their AI initiatives while reducing costs tied to data transmission and cloud storage.
2025 will see AI applications that enable teams to manage their data, analyze documents, and refine workflows in real-time, without overhauling existing infrastructure. By adopting a practical approach to AI, businesses can integrate these tools to drive competitive advantages in an ethical, transparent manner. The focus on democratized, agent-driven AI highlights a future where powerful technology is not just for the few but is available to organizations everywhere, transforming industries, elevating productivity, and setting new standards in accessibility.