- Download Culture Report•Workplace Culture in 2025 and What it Signals for 2026
Artificial Intelligence (AI) refers to the simulation of human intelligence by computer systems and algorithms. These systems are designed to learn from data, make predictions, automate decision-making, and solve complex problems. In the workplace, AI tools are increasingly used to boost productivity, streamline operations, and provide deeper insights into organizational trends.
Emtrain’s harassment training course is engaging, interactive, and designed to spot and reduce EEO risk.
Artificial Intelligence is not a single technology, but a set of approaches that includes machine learning, natural language processing, predictive analytics, and computer vision. These capabilities enable organizations to automate tasks, analyze vast amounts of data, and improve decision-making.
Artificial Intelligence is moving quickly from concept to everyday practice, and employees across industries are finding practical ways to integrate AI into their daily work. From automating routine tasks to generating creative ideas and supporting complex decision-making, AI tools are reshaping how offices operate. Below is a table of real-world examples that highlight how employees are currently using AI in the workplace, what those applications look like in action, and the impact they are having on productivity, efficiency, and collaboration.
| Use-Case / Trend | What It Looks Like / Example | Why It’s Being Used / Impact |
|---|---|---|
| Idea generation & creative work | Employees are using tools like ChatGPT (and similar generative language models) to help draft content: emails, social media posts, ad copy, lesson plans, etc. E.g. marketing teams, educators use AI to brainstorm or draft first versions. (Business Insider) | Speeds up content creation, reduces writer’s block, frees up time for refinement rather than starting from scratch. |
| Information consolidation & summarization | Pulling together data reports, summarizing documents or meetings, aggregating feedback or research—AI tools that synthesize large inputs. (Gallup.com) | Helps reduce manual labor in reviewing many sources, helps leaders or teams get up to speed fast, supports decision–making. |
| Automating repetitive tasks / basic workflows | Tasks like scheduling, email triage, formatting reports or spreadsheets, auto-responses, basic data entry. Also HR tasks like shortlisting resumes or screening initial candidates. (New Horizons) | Frees employees from repetitive/non-value-added work, reduces error or bottlenecks, allows more focus on strategic or interpersonal work. |
| Decision support & analytics | Using predictive analytics, scenario modeling, risk-assessment tools; tools that suggest options rather than making the decision outright. For example, finance teams using AI to model forecasts, tax implications, or revenue trends. (The Wall Street Journal) | Helps with making more informed decisions faster, better handling of complex or data-heavy problems where human calculation would be slow or error-prone. |
| Hiring, HR & talent management | AI used in screening resumes, finding candidate profiles (including through generative AI tools), simulating interviews (feedback tools), measuring engagement or sentiment. Walmart’s Chief People Officer, for example, is using tools to surface leadership candidate profiles. (Business Insider) | Makes hiring more efficient, can support fairness if done well, saves time and cost, scales talent processes. |
| Personal productivity assistants | Virtual assistants, scheduling meetings automatically, summarizing long documents, smart email suggestions, reminders, task-prioritization tools. (Tettra) | Helps employees manage workloads, reduces cognitive overload, improves time management and efficiency. |
| “Shadow AI” / unofficial adoption | Employees are using AI tools privately or without explicit permission; for example, using ChatGPT or other public tools to help with job tasks even when company policy is vague or restrictive. Some hide use from managers. (Business Insider) | Shows demand for AI tools is strong; reflects gaps in policy, training or trust; but can introduce risks (data leakage, accuracy, misuse). |
| Workplace communication & collaboration enhancements | AI-powered chatbots, virtual assistants, tools that suggest next steps, tools that summarize meeting or chat conversations, help with knowledge sharing (recommend related documents, FAQ generation). (Tettra) | Makes collaboration more efficient, reduces silos, helps bring new hires or other team members up-to-speed faster, helps reduce friction in information handoffs. |
Opportunities:
Increased efficiency and productivity
Enhanced data-driven decision-making
Improved employee experiences through personalization
Cost reduction and operational savings
Scalability of compliance monitoring
Risks:
Bias in algorithms leading to discrimination
Data privacy and security concerns
Over-reliance on automated decision-making
Reduced human oversight in critical areas
Job displacement or employee mistrust
Practical Guide for Navigating the AI Workplace Frontier
Download this guide and learn how HR can lead the way on Ethical AI.
Enterprise AI Governance Policy Template
Get a ready-to-use Responsible AI policy template to manage compliance, privacy, and ethics—helping leaders adopt AI safely and responsibly.
Bias in AI: How to Identify and Prevent Discrimination
Learn how to identify and prevent bias in AI. This is an important matter as using AI in the workplace is rising in popularity.
AI Surveillance in the Workplace
AI surveillance is becoming more popular in the workplace. However, this brings into question how much AI surveillance is too much?
How Can AI Be Used in the Workplace?
How can AI be used in the workplace? Read to find out different ways AI can be utilized in the workplace for better efficiency.
The Pros and Cons of AI in the Workplace
Learn how AI boosts productivity, saves costs, and improves safety—while exploring risks like job displacement, ethics, and security.
Watch this workplace scenario when an employee uses client data in AI to make a report on expansion and churn data. Thinking she be more productive she forgot that putting client info into a third party tool could expose that information to the public.
