AI Tools Across Job Functions: 2025 Guide to Using AI for Work

AI has morphed from speculative tech to an essential co-worker so swiftly that even the most stubborn technophobes are begrudgingly asking ChatGPT for help with their PowerPoints. According to McKinsey, 92% of organizations plan to increase their AI investments over the next three years. 

This isn't a fad like treadmill desks. It's a fundamental recalibration of how work gets done, like email. The AI revolution has spilled beyond the confines of tech departments and data science teams, with specialized applications now enhancing (and occasionally complicating) almost every professional function. It might not take your job, like some fear, but if you’re the only one not using it… good luck. 

Only 1% of businesses consider themselves at maturity with AI so far, McKinsey reports. That’s not entirely surprising, considering how new most AI software is. It also means there’s an opportunity to beat the competition to successful AI adoption and gain an edge.

In this guide, we'll traverse the increasingly crowded landscape of AI tools, department by department. Consider this your map through the wilderness of options. Equal parts field guide and survival manual for the AI-augmented workplace, we hope this will give you the lay of the land and guide your continued exploration of our brave new professional world.

Practical Applications of AI Tools

We’re not here to contribute to the discourse around whether AI will save humanity or destroy it. While the hysterics are interesting, it’s more helpful to focus on what we can control. AI persists regardless of our personal views, so it’s time to take a pragmatic look at how these tools fit into our daily work.

There are dozens of new AI tools popping up every day. At their core, you can generally find some combination of three key capabilities:

• Natural language processing – AI applications understand and generate human language, and they’re already better than some of our coworkers (no offense, Frank).
• Machine learning – These systems improve their performance and adapt to change without explicit programming or commands.
• Predictive analytics – These tools forecast future outcomes based on historical data.

We don’t know how or when AI will replace humans. For now, let’s look at some ways these capabilities help robots take the parts of our jobs we never liked anyway. This list is not comprehensive. It’s only intended to help you start your search, depending on the job function you want AI to take on.

General Productivity AI Tools

These AI tools transcend departmental boundaries. You can think of them as digital assistants that make almost anyone more effective, regardless of their specific role.

• ChatGPT – This all-purpose thinking companion from OpenAI generates everything from blog posts to code snippets. 
• Claude – Anthropic’s all-purpose AI assistant excels at nuanced writing tasks and complex reasoning with fewer hallucinations than its OpenAI counterpart (according to Claude 3.7 Sonnet, which helped me organize my research for this post).
• Gemini – Google’s AI is particularly adept at research and fact-based content creation, which makes sense coming from the world’s favorite search engine. It offers convenient integration with the rest of Google's ecosystem.
• Notion AI – The note-taking and knowledge management system has transformed with AI-powered summaries, action item extraction, and writing assistance.
• Grammarly – This popular writing assistant uses AI to analyze your text and make suggestions for clarity, accuracy, and style.
• Otter.ai – Use this AI meeting agent to get transcriptions, notes, and action items from all of your meetings.

The trick with these general-purpose AI tools isn't just finding them—most professionals we know are already using at least one–but integrating them seamlessly into your workflow. For example, you can start with one tedious task like summarizing meeting notes, drafting routine emails, or organizing research.

Let the AI handle the first version, then bring your human judgment to refine and finalize. Even if AI produces something that doesn’t meet your standards, it’s helped you get started, which is the hardest part. Once you’re comfortable using it for the first task you selected, you’re ready to expand your use of AI.

Marketing AI Tools

Marketing blends art and science, and AI rises manages the balance surprisingly well. You might expect AI to handle the analytical side with ease, but it’s also acquired a scarily decent grasp on expressiveness and metaphor in recent months.

• Sprout Social – Streamlines social media management with AI-powered analytics that identify engagement patterns and content opportunities your human eyes might miss
• Albert.ai – Autonomously optimizes digital advertising, adjusting campaigns in real-time to maximize performance
• Optimove – Leverages AI for CRM hyper-segmentation that identifies microsegments in your customer base for targeted campaigns
• Copy.ai – Generates marketing in your brand voice and automates parts of your GTM engine
• Marky – Recently featured on AppSumo, this tool automates content creation and scheduling for social media
• KPAI – Uses programmatic technology and artificial intelligence to optimize media planning and retargeting

Creative applications of AI for marketing are transforming how brands connect with audiences, and not just at hip new SaaS companies. Mercedes-Benz's "Moody Colors of Poland" campaign used AI to analyze social media posts containing emotional language, identifying patterns that informed a color-themed marketing initiative linked to their vehicle's ambient lighting options.

The greatest challenge of using AI for marketing is maintaining authenticity and humanity. The most successful approaches use AI as the creative sous-chef, not the head chef. It preps the ingredients, but human marketers determine the flavor and presentation.

Sales AI Tools

At its core, sales is about human relationships. Still, AI is making an impact here:

• Salesforce Einstein – Predicts which deals are most likely to close so sales teams can focus their efforts
• Cognism – Supercharges prospecting and lead generation by identifying potential customers
• Salesloft – Automates sales engagement workflows while providing intelligence on what messaging resonates

Again, the challenge is to maintain the human touch while leveraging these AI sales tools. The best teams use technology to expedite the mechanical aspects of sales (research, data entry, rote task execution) while freeing human salespeople to focus on relationship building and problem-solving.

If you want to test this, roll it out to part of your sales team as a trial. Then, track increases in pipeline velocity, conversion rates, and average deal size.

Development and Software Engineering AI Tools

It seems ironic that software engineers have started to replace parts of their own jobs with AI, but maybe it shouldn’t really be surprising. After all, the people with the knowledge to create AI software used it to take care of the tasks they’re most familiar with:

• GitHub Copilot – Serves as your pair programming AI that suggests code completions and sometimes entire functions as you type
• Cursor – Provides AI-assisted coding with context-aware understanding of your entire codebase
• Windsurf – Generates and reviews code with impressive accuracy when you bring your own API keys
• Aider – Functions as an autonomous coding assistant that understands project context beyond single files

Beware, though, AI models were trained on massive amounts of human code, not just the good stuff. AI easily handles boilerplate code, but it probably won’t build the next tech unicorn by itself. Keep a human in the loop to watch out for bugs, security vulnerabilities, and logical errors. Humans still seem better at systems thinking, architectural design, and algorithm creation.

Data Analytics AI Tools

Not long ago, "data-driven" meant spending 70% of your time wrangling spreadsheets and 29.9% designing visualizations that executives would glance at for precisely 2.7 seconds. The final 0.1% was for quiet despair. Today’s AI tools, if nothing else, save you more time for a good frustration cry.

• Tableau with Einstein – Doesn't just visualize your data but practically psychoanalyzes it, revealing insights you didn't know to look for while generating the visualization your executive actually needs
• DataRobot – Democratizes machine learning for those of us who don't dream in Python, automating predictive models that once required a PhD and a concerning caffeine dependency
• Power BI with AI capabilities – Microsoft's offering that transforms your spreadsheet nightmares into interactive dashboards while deciphering patterns mere mortals would miss

These tools aren't simply faster calculators. They're becoming cognitive partners that free analysts from data plumbing to focus on the art of asking the right questions and contextualizing answers. A spreadsheet can tell you what the data says, but you still decide what to do about it.

People Operations and HR AI Tools

The human element is literally in the name of this department, but there are a ton of AI tools to take care of HR work:

• Rippling – Talent Signal evaluates employee performance and provides actionable feedback using empirical analysis of work outputs, not just managerial opinions. Ripling FP&A provides data-driven workforce analytics and planning to optimize headcount and skills distribution.
• TestGorilla – This talent management assistant streamlines skills assessment with automated, bias-reduced candidate screening.
• Lever – Use this integrated applicant tracking system and candidate relationship manager to automate workflows like job posting and resume parsing.

There are ethical considerations here, especially around bias mitigation, transparency, and privacy. If you don’t care about ethics, do the right thing for risk management purposes. As with anything else, it’s probably best to start by using AI for low-risk admin functions before moving on to sensitive applications like performance evaluation or hiring. Maintain human oversight and audit outcomes for unintended consequences.

Finance and Accounting AI Tools

Finance departments were among the earliest adopters of other technology tools (back when you had time to refill your coffee while the Excel function churned away). Now they’re at the forefront of AI implementation, too:

• Datarails FP&A Genius – Transforms financial planning with conversational AI that operates on real-time consolidated financial data
• Nanonets – Automates invoice processing and accounts payable workflows with remarkable accuracy
• Planful Predict – Forecasts financial outcomes and enables sophisticated scenario planning
• Cube – Streamlines financial modeling with automated data integration from multiple sources

Compliance considerations are paramount in finance AI implementations. The good news is that many of these tools are built with regulatory requirements in mind, producing audit trails and documentation to satisfy regulators. The use cases here are especially compelling, too, because which department cares more about ROI and cost reduction?

Business Operations AI Tools

Operations—the often underappreciated backbone of organizational efficiency—may have the most to gain from AI automation.

• Activepieces – Enables no-code business automation without sending your data to third parties
• Zapier – Uses increasingly sophisticated AI enhancements as it connects apps and automates workflows
• Fellow – Centralize meeting recordings, notes, and summaries with an AI meeting assistant

Streamlining operations with AI requires a systematic analysis of your current workflows. You might start by documenting your current processes, identifying bottlenecks and repetitive tasks, then evaluating which AI tools could address those specific challenges. 

For example, a logistics company might use AI to optimize routes, saving time and fuel costs. A healthcare company might be more concerned with AI scheduling and appointment reminders to free up staff and reduce no-shows.

Predictive Analysis of the Future of Workplace AI

The rise of AI tools is already remarkable, but we're still at the very beginning of this shift. Emerging trends suggest where things might be heading next:

1. Agentic AI – More autonomous tools that can complete multi-step processes with minimal human oversight
2. Domain-specific large language models – Tools tailored to specific industries (or even organizations) with deep expertise in particular fields
3. Collaborative intelligence – AI systems designed to work together in teams, both with other AI tools and with humans
4. Democratized AI development – Increasingly accessible tools for non-technical users to create custom AI solutions

Organizations that view AI as a complement to their employees will form successful partnerships between humans and machines. Looking for opportunities to replace humans might cut costs. Using AI to amplify human capabilities and compensate for our shortcomings will unlock a whole new way of working.

Beyond the Shiny Object Syndrome – Implementation Strategy & Best Practices

Successful implementation of AI tools isn’t as easy as buying licenses and turning your teams loose. Consider a more thoughtful implementation framework:

1. Start with strategy, not tools – Identify specific business problems you're trying to solve before selecting AI solutions.
2. Begin with pilot projects – Test tools in contained environments before broader rollout.
3. Invest in training – Ensure your team understands how to use the tools, especially their limitations. AI tools occasionally make up facts with impressive confidence. Keeping a human in the loop will help catch these hallucinations before they embarrass you (or worse).
4. Establish governance – Create clear policies around AI use, particularly regarding data security and decision authority.
5. Measure and refine – Establish clear metrics for success and continuously improve your implementation.

Security and data privacy deserve special attention throughout the process. Evaluate each tool's approach to data storage, encryption, and compliance with relevant regulations. You might even create data classification policies that determine what information can be processed by AI tools. Like any other part of your business, it’s worth making intentional decisions about how you’ll use these tools.

Using AI Tools to Create an Augmented Workplace

Everyone can decide for themselves what the AI revolution is about. For some, maybe it’s only about replacing human workers to save some money on payroll. For us at Sketch, it’s more about redefining what human work can be. 

Offloading routine tasks to machines creates more space for more creative, strategic, innovative contributions. We’re in the software industry, but the same can be said for any product development effort: When you’re building something for humans, the human experience should be at the center of your design.

AI doesn’t understand the human experience. It also can’t achieve true creativity. These models are trained on what is and what has been. They don’t have the human ability to conjure a vision of a better future.

The organizations with the most advanced AI tools won’t necessarily be the most successful. Thoughtful integration of AI tools into human workflows will separate winners from losers. Knowing what AI can do is a good start. The real question is this: "What can humans do better when augmented by AI?"

So, which AI tool will you implement first? As always, the answer should depend on the desired outcomes rather than the flashiest features. Whether you build or buy, we recommend making choices to address your most pressing business challenges and complement your team's unique strengths.

We don’t think the future of work is human versus machine. It's human and machine versus problems we couldn't solve before.

What AI tools have transformed your workflow? Contact us to let us know what this article is missing, or to talk shop about custom AI implementations.