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9 powerful ways legal, finance, and HR can use AI

When you think of AI at work, it’s easy to picture marketers drafting blog posts or crafting social media content. But AI’s possibilities go beyond marketing. In fact, some of the most revolutionary uses of AI are happening in traditionally less front-facing roles such as legal, finance, and HR.

These departments are the backbone of any organization, handling complex tasks that require precision, analysis, and judgment. AI’s capabilities in these areas can save countless hours, minimize errors, and help teams make decisions more efficiently.

Let’s explore nine ways in which legal, finance, and HR departments can take advantage of the power of AI to transform their workflows.

Legal: AI tools for efficiency and precision

Streamline contract summaries

Contracts are often long, dense, and packed with legal jargon, but AI can simplify this process. Tools powered by AI can summarize contracts into plain English, highlight unusual clauses, and flag high-risk terms. Want to compare contract versions? Ask an AI tool to identify key changes, saving paralegals and attorneys hours of tedious work.

Example prompt:

“Compare these two versions of the vendor agreement and highlight differences in termination clauses.”

Draft policies

Writing legal policies, such as Acceptable Use Policies or Non-Disclosure Agreements, is time-consuming. AI can take your specific requirements and generate a solid first draft, which you can refine for tone and compliance.

Example prompt:

“Write a GDPR-compliant NDA in a friendly but professional tone.”

Translate legal documents

Whether expanding globally or dealing with international clients, language barriers can be an issue. AI-enabled language tools can translate policies and contracts efficiently, saving you days of waiting on manual translations.

Finance: AI simplifying reports and forecasting

Automate monthly reports

Every finance professional knows the struggle of analyzing and retrieving insights out of spreadsheet data. AI simplifies this process by turning numbers into concise, actionable written summaries. With just a few keystrokes, your month-end report can be ready.

Example prompt:

“Summarize the revenue and expense data in this spreadsheet. Highlight any anomalies.”

Spot financial anomalies

AI-powered tools are great at analyzing complex datasets to flag duplicate entries, high-value transactions missing documentation, or irregular patterns in spending. For auditors and accountants, this acts as an efficient second pair of eyes.

Example prompt:

“Identify transactions over $3,000 in this expense report that don’t have a matching purchase order.”

Pro tip: You can even upload your expense policy and a screenshot of a receipt and ask AI to see if the two are compatible.

Create cash flow forecasts

Analyzing financial projections takes time and expertise, but AI can run the numbers and generate forecast summaries with assumptions clearly outlined.

Example prompt:

“Use the given revenue and expense projections to create a three-month cash flow report.”

HR: AI enhancing recruiting and employee retention

Craft effective job descriptions

Recruiting top talent often starts with an engaging job post. AI can write job listings tailored to specific roles, company culture, and diversity goals, saving recruiters time and improving hiring outcomes.

Example prompt:

“Create a job description for a remote junior software engineer focusing on growth opportunities.”

Develop targeted interview questions

AI supports HR professionals by crafting custom interview questions. Whether you need questions for specific roles or particular skills, AI helps focus the conversation where it matters most.

Example prompt:

“Generate five behavioral interview questions for a project manager emphasizing leadership and adaptability.”

Another pro tip: Upload the job description and a candidate’s resume and have AI spot where the candidate’s skills align and where there could potentially be gaps. It’s still up to you to dig deeper during the interview (don’t outsource your interviewing and people skills), but this can give you some things to think about.

Summarize employee feedback

Employee satisfaction surveys and performance reviews often include valuable insights, but parsing through endless responses can be overwhelming. AI tools can identify recurring themes and summarize findings, providing actionable insights in minutes.

Example prompt:

“Summarize strengths and challenges mentioned in these employee reviews.”

Create personalized onboarding plans

Effective onboarding is key to retention. AI can help HR teams design tailored onboarding programs by factoring in the employee’s role, location, and team structure. Here’s a more in-depth post on this subject..

Example prompt:

“Design a 30-day onboarding plan for a Customer Success Manager that includes training, shadowing, and performance check-ins.”

Risks and pitfalls to consider while using AI

While AI offers game-changing potential, it’s not without its challenges. Here are some key risks to keep in mind when integrating AI into your business functions.

Hallucinations and errors

AI can sometimes provide inaccurate or overly confident responses, particularly in legal, financial, or compliance scenarios. Always double-check AI-generated outputs to ensure accuracy.

Loss of context

AI tools need precise, well-organized data to deliver meaningful results. Vague or overly general prompts can produce irrelevant or misleading results.

Be detailed in your instructions, and ensure all necessary context is provided.

Data privacy concerns

Many AI tools rely on cloud-based systems, meaning any data you input is stored or processed externally. Avoid pasting sensitive information into tools without clear data privacy policies, or consider enterprise-grade AI solutions with stronger security measures.

Potential bias

AI tools trained on public datasets may unintentionally replicate biases present in the data. Use tools designed for fairness to eliminate potential bias in job descriptions, performance reviews, or customer-facing policies.

Wrap-up

Automation technology like AI doesn’t aim to replace professionals. Rather, it acts as an invaluable assistant. Think of AI as your fastest, most focused assistant, quick to get things moving but still reliant on your expertise for the best results.

By leveraging AI, you can drastically cut down on repetitive tasks, streamline complexity, and empower your team to focus on high-impact work. Transforming departments like legal, finance, and HR has never been easier, or more essential, in staying ahead in today’s fast-paced business world.

What about you? What are your favorite use cases of AI in “the back office”?

empty meeting room with an AI bot hovering over the table

Are AI notetakers helping or hurting your meetings?

It feels like every other week a new AI tool pops up, promising to “make meetings effortless, saving you hundreds of hours.” One of the hottest right now is AI notetakers. Tools that join your Zoom, Teams, or Google Meet, quietly record the call, and then generate a transcript and summary for you.

In theory, it sounds amazing. No more frantic typing. No more “Wait. What did they say about that deadline/that feature request?” You can actually sit back and be present.

I was a rabid fan when I started using them. But, like most shiny new AI helpers, it’s not all upside.

The positives

You’ll never miss a detail again
Having a transcript is great if someone misses a meeting or if you just want to check back on who agreed to what. From an accountability standpoint, that is a huge plus.

Freedom to actually listen
Instead of scribbling notes, you can make eye contact the entire time and really focus on the conversation, knowing the AI will capture it all.

Great for remote teams
When your teammates are spread across time zones, having a neat summary waiting in Slack or email can keep everyone aligned without another meeting.

So far so good.

Where it gets messy

People clam up
The moment you tell a customer, “By the way, we’re recording this,” the tone often changes. They’re less likely to be brutally honest about what isn’t working. That’s obviously a problem if you actually want the truth.

Things become performative
The opposite can also happen: instead of clamming up, people sometimes go into “stage mode” when they know they’re being recorded. They perform instead of just talking, which makes the whole meeting feel less authentic.

You stop taking your own notes
There’s something about writing things down that makes your brain hold onto them better. If you just rely on AI, you’re outsourcing not just the notes but your memory. I can certainly attest to that. I remember more details from meetings I had pre-notetaker compared to the ones where I had it running.

You over-rely on other people’s discussions
If you care about delivering the right products and services to your customers, you can’t just lurk in transcripts of meetings you weren’t in. You need to talk to customers yourself frequently (here’s more on the subject). You know best what insights you want, and you’ll never get the same clarity secondhand.

Coaching gets robotic
It’s tempting to let AI summaries or call insights do the work of coaching sales reps and customer success managers. But AI can’t detect subtle hesitations, awkward silences, or emotional tones that matter in human relationships. Leaders still need to guide and mentor, especially since AI doesn’t have the same context as you when it comes to organizational history, challenges, or your relationship with a customer.

AI can’t read the room
Yes, it knows what was said. But it has no clue how it was said. That subtle sarcasm? Gone. The change in tone? Undetected. The tension you felt when someone crossed their arms? Can’t be found in the notes.

Not every meeting needs a transcript
Sometimes it’s overkill. Recording everything can make people feel like they’re under surveillance. And honestly, it can be a massive distraction. Plus, it’s a time sink when people start digging through meetings they weren’t even in just out of curiosity.

Privacy risks are real
You’re storing transcripts of strategy calls, customer complaints, even HR issues. Those are sensitive topics, and they need to be treated with care, or it could come back to bite you.

Is there a middle ground?

To be clear, I’m not anti-AI notetaker. They can be lifesavers in the right situation. But like most tools, the value depends on how you use them.

Ask yourself:

Do we really need this meeting recorded?
Will it make people less likely to share openly?
Am I letting AI make me lazy?

If the answer to any of those is “yes,” maybe leave the bot out of it.

AI notetakers are like that super-organized friend who always remembers the details. They’re great to have around, but you don’t want to rely on them so much that you stop paying attention yourself.

Meetings are, at their core, about humans connecting problem-solving, and helping each other . Let’s not lose that just because a bot can spit out bullet points.

What about you? Do you find that AI-notetakers help or hurt your meetings?

Thank you for your (current) shortcomings, AI

AI dominates today’s business conversations. Companies are pouring billions into tools that write, analyze, and automate. But the leaders who thrive aren’t those who blindly outsource to machines. They’re the ones who recognize AI’s limits and lean into the distinctly human strengths that technology can’t touch, at least not yet.

As leadership expert Cy Wakeman reminds us, “Your circumstances aren’t the reason you can’t succeed. They’re the reality in which you must succeed.” AI isn’t the obstacle. It’s the reality. Your edge as a leader comes from doubling down on what AI can’t do.

1. Context over data

AI is fantastic at processing information, but it doesn’t live in your organization. It can’t read the silence in a tense meeting, recall the project that failed (but succeeded to traumatize your team members) two years ago, or understand that one employee’s informal influence outweighs their job title.

Satya Nadella has described AI as a “copilot, not an autopilot.” That distinction matters. Leaders who know their company’s culture, history, and unwritten rules can make calls no algorithm could ever justify in a spreadsheet.

2. Inspiration instead of automation

AI can generate motivational text on command. But true inspiration isn’t written. It’s experienced. It comes from leaders who rally a team through uncertainty, or who celebrate a small breakthrough that carries months of weight.

Empathy requires sensing what’s said and what’s left unsaid. It means taking a struggling employee out for coffee, or lowering the temperature in a tense room. Those moments build culture and commitment. As Wakeman teaches, great leaders skip the drama and connect people back to reality and purpose.

3. Values-based judgment

AI will show you probabilities. It won’t show you principles. Leaders make decisions where the “optimal” answer isn’t the right one, where cutting costs might please the board but result in burnout on your team.

Google’s Sundar Pichai has called AI “more profound than fire or electricity.” If that’s true, then leaders need to be the firebreak: using judgment, ethics, and values to ensure the power of AI serves people, not the other way around.

4. Trust through humanity

Trust doesn’t live in dashboards or reports. It grows in hallway conversations, after hours crisis calls, and moments where leaders admit they don’t have the answer.

Consistency, vulnerability, and care build psychological safety. Can this be automated? Not now, at least. AI can give your team information faster, but only you can make them feel safe enough to share the truth.

5. Vision beyond the data

AI predicts the future by analyzing the past. But breakthrough innovation requires imagination. Leaders must see possibilities no dataset can show. Think of the iPhone before the iPhone, or the electric car before it was mainstream.

In Contact, when scientist Ellie Arroway witnesses a cosmic spectacle too beautiful for words, she says: “They should have sent a poet.” Even with all our technology, some things require human awe, artistry, and vision. (Fittingly, OpenAI is currently hiring poets: it turns out machines still need us to make sense of wonder.)

The leadership advantage

Understanding AI’s limits reveals where leaders should focus: contextual intelligence, emotional intelligence, values, trust, and vision. AI offers speed and scale, while humans offer meaning and direction.

Organizations that integrate both (using AI as a copilot while leaders lean into uniquely human strengths) will outperform those that rely too heavily on either side alone. The gift isn’t what AI can do. The gift is what it can’t, and the space it leaves for leaders to show up more fully human.

What about you? Which shortcomings of AI do you see not as flaws, but as your opportunity to lead differently?

Looking at constraints as a positive

Most people see constraints as obstacles to overcome. But what if your biggest limitations might actually be your greatest opportunities for breakthrough thinking and meaningful progress?

When resources are scarce, deadlines are tight, and options feel limited, our natural instinct is to focus on what we can’t do. We get stuck in frustration mode, wishing we had more time, more budget, more resources, or more freedom. But this mindset misses a fundamental truth: constraints don’t just limit us. They can actually be liberating.

Hear me out.

Don’t underestimate the power of limitations

Constraints force us to think differently. They strip away the paralysis of infinite options and demand focus on what truly matters. When you can’t do everything, you’re forced to do the right things really well.

Consider the most innovative solutions you’ve encountered. Chances are, many emerged not in spite of constraints, but because of them. Look at all the innovations and pivots that happened during COVID!

Take Georgia State University, for example. When in-person orientation was canceled during COVID lockdowns, they didn’t try to replicate the traditional experience with clunky Zoom calls. Instead, they launched a gamified digital orientation that used mobile apps, behavioral nudges, and personalized messaging to walk students through everything from class registration to financial aid. Not only did engagement increase, but the infrastructure they built continues to support hybrid orientation year-round. The constraint became a springboard for deeper personalization and better outcomes.

Or look at Little Sesame, a Mediterranean fast-casual restaurant in Washington, D.C. When they had to shut their doors, they could’ve waited it out. But instead, they pivoted to launch “Hummus at Home” meal kits, a creative way to bring their brand into customers’ homes. They paired that with a community initiative called “Feed the People,” delivering free meals to frontline workers and local families. In the process, they built a new revenue stream, expanded their customer base, and deepened their brand’s emotional resonance.

These are perfect examples of how constraints can channel creative energy into focused, high-impact solutions. When limitations demand better thinking, organizations often uncover approaches they wouldn’t have considered in times of abundance.

How constraints may foster better thinking

When facing unlimited options, we often freeze. Research shows that too many choices can lead to decision fatigue and decreased satisfaction. Constraints narrow our focus to what’s actually possible and important.

With limited resources, you can’t pursue every good idea. Instead, you must identify what matters most. This forced prioritization often reveals insights that would remain hidden in environments with excess.

Constraints make us more creative with what we have. When the usual solutions aren’t available, we’re pushed to find novel approaches, repurpose existing resources, or discover efficiencies we never knew existed.

Shifting Your Constraint Mindset

The key to leveraging constraints isn’t to pretend they don’t exist or to simply “think positive.” It’s to fundamentally shift how you relate to them.

“I Can’t” -> “How Might I?”

Instead of focusing on what constraints prevent, ask what they make possible. What new approaches do they open up? What assumptions do they force you to challenge?

Problem -> Parameter

Treat constraints as design parameters rather than problems to solve. If you’re building a house, the lot size isn’t a problem—it’s a boundary that shapes your design. Apply the same thinking to your professional limitations.

Scarcity -> Focus

Reframe limited resources as focused resources. When you can’t do everything, you get the rare chance to do the right things exceptionally well.

How you talk about constraints matters.

In my post “Venting: The Not-So-Silent Culture Killer”, I explored how habitual complaining creates a ripple effect of powerlessness. When we vent about constraints without reframing them, we reinforce the idea that we’re stuck. But when we treat constraints as catalysts, we reclaim the narrative and the power.

Getting started

Embrace “good enough”: Perfectionism and constraints rarely coexist. Often, a good-enough solution delivered on time and within budget is far more valuable than a perfect one that’s too expensive or too late.

Look for unconventional resources: When traditional resources are limited, think creatively. Can you partner with another team? Leverage user-generated content? Build a minimum viable version first? Let your constraint spark resourcefulness.

Question assumptions: Constraints surface hidden assumptions. Use them as prompts to challenge standard approaches and uncover new paths.

Use and build on what you have: Inventory what’s already working. Often, progress comes not from acquiring more, but from better using what you already have.

Even in the most constrained situations, you retain control over your response. You can’t always change your circumstances, but you can change how you approach them.

As noted in “Developing Resilience in the Face of Adversity”, focusing on your locus of control is essential to both personal effectiveness and professional impact. When you shift from lamenting constraints to leveraging them, you unlock a form of agency that’s deeply energizing.

When a constraint shows up, pause before defaulting to frustration. Ask:

What does this limitation force me to focus on?
What creative solutions does this constraint make necessary?
How might this restriction lead to a better outcome?

Keep a record of times when limitations actually led to better solutions. This helps build confidence that the next constraint could be a new opportunity.

And when you see colleagues struggling with limitations, share your own constraint-to-clarity stories. This builds a culture that sees possibility where others see barriers.

What about you? When have you benefitted from a constraint?

sticky notes with yes and no written on them

Why saying no by default is not a strategy

Saying no can be liberating. It’s a word that leaders, product managers, and founders often use as their shield against scope creep, burnout, and loss of focus. Yet, I wonder if the real art isn’t about defaulting to a firm no. It’s about knowing why you’re saying no, understanding the impact, and being open to other paths when possible. What if we can shift from knee-jerk rejections to meaningful, strategic decisions that serve both our business and our customers.

Why revisiting our no matters

It’s been years since I explored why we shouldn’t shy away from saying no to projects, features, or deals that don’t align with our vision. But time and experience have shown me that “no” is not a free pass out of tough conversations. Nor does it automatically mean you’re operating in the best interests of your team or users. The nuance lies in the decision-making process and the honesty behind it.

With over a billion results for “saying no to a feature request,” the topic is far from new. Yet, many teams still struggle to move beyond a templated refusal, missing out on growth, innovation, and customer goodwill in the process.

Identify the real reason behind your no

Be honest with yourself

Before saying no, dig deeper. Is your answer rooted in what’s truly best for your product and customers? Or are you being swayed by something less objective, like risk averseness, internal bandwidth issues, or personal bias? Sometimes, a quick refusal feels safer than challenging assumptions or pushing your team outside their comfort zone.

Tracking your decisions helps. Document every no and, more importantly, the reason behind it. This reflection gives you valuable data, helping you spot patterns like resisting new ideas, underestimating team capacity, or playing it too safe. You might discover that your “no” is occasionally more about your own limits than your customers’ needs.

Separate product needs from personal preferences

Maybe a feature request sounds wrong simply because it’s not what you’d want as a user. Or maybe a contract term feels risky, but you haven’t weighed the potential upside. By being transparent, you open up space for objective analysis.

Here’s an idea. Start an internal “no log.” When you turn down a request, capture what was asked, why you’re declining, and the true business reason. After a quarter, review for trends or missed opportunities.

No doesn’t always mean never

Consider no, but add “but”

The word no doesn’t have to be a conversation-ender. Sometimes, a flat rejection is appropriate. More often, a “no, but…” unlocks better dialogue and creative alternatives.

Contract terms: Maybe you can’t agree to everything the partner asks, but could you offer a concession elsewhere?
Feature requests: If a proposed feature isn’t feasible, could an integration with another tool help your customer achieve the same outcome?
Project proposals: Resource-constrained? Suggest a partnership with a trusted contractor instead of rejecting the project outright.

Whenever you deliver a “no,” challenge yourself to also offer a workaround, a timeline for revisiting, or a different way forward. You’ll build trust and demonstrate that you’re listening.

Weigh the consequences of saying no

Balance ROI with opportunity cost

Rejecting a new idea or feature is rarely risk-free. Of course you should ask, “What will this bring us?” But you must also flip the question: “What could we lose by turning this down?” Each no closes a door, possibly for good.

Could refusing a feature be the difference between keeping and losing key customers?
Is turning down a contract leaving money and future partnerships on the table?
Will a pattern of no responses become a reputation risk over time?

For example, a SaaS platform might skip a small feature to focus on core improvements. But if that feature is critical to a cluster of customers in a lucrative segment, the opportunity cost could outweigh the savings.

With every major no, write a short post-mortem. Review both the intended gains and potential losses, and discuss as a team before finalizing.

Stay flexible as context changes

Adapt your no to the times

Business climates evolve. That means your “no’s” should, too. Maybe last year you avoided broad integrations because of limited resources, but now, economic shifts or new partnerships demand a more open approach.

Are current market or global trends changing customer expectations?
Has a new law or regulation made your earlier decision irrelevant?
Could tighter budgets mean you revisit previously shelved ideas that now look more viable?

As leaders, we need to widen our lens to include industry shifts, economic downturns, and even global crises. What was a hard no yesterday might be a qualified yes, a “maybe” with caveats, or a “no, but” today.

Regularly revisit your default responses. At your quarterly strategy review, ask, “Is our no still the right answer given what’s changed?”

Align the best for customer and company

There’s nothing weak about turning down a customer, a feature, or a contract term. What matters is that your decision aligns with long-term goals for both your company and the people you serve. These interests are not opposing forces. The sweet spot is where they overlap.

Make decisions with transparency.
Communicate your reasoning.
Demonstrate that you’ve weighed impacts on all sides.

When your team and your customers see that your no’s are principled instead of arbitrary or reactionary, they’re far more likely to stick with you.

Let’s rethink our relationship with “no.” The next time you’re asked for a feature, project, or partnership, pause before defaulting to a refusal.

Track and analyze your decisions for hidden patterns.
Look for “no, but” opportunities wherever possible.
Evaluate both the costs and opportunities of every no.
Stay alert to shifts, from market sentiment to legislative changes.
Be transparent with your reasoning, building credibility inside and out.

Saying no is an essential leadership tool. But it’s a scalpel, not a sledgehammer. Use it to cut out what’s unnecessary, not to block growth, innovation, or trust.

What about you? How have your views on saying no changed as your context has evolved?