AI has completely transformed our team at Paintit.ai both from a product perspective and behind the scenes. The upside of this is we have converted a process that took weeks for interior design into a 30 second experience. Users submit a photo of the room they want to redesign, and instantly they receive a unique visual redesign they might want to use based on their style and layout. In a way we are giving users access to a designer, on demand and on a budget. This simply never would have happened before. Now the downside: AI is only as good as the data it provides and the context it is shown in. We have battled the idea that "AI = always perfect." It always needs human curation as it relates to nuance with architectural bounds or cultural aesthetics. We have spent an extraordinary amount of time training our system, avoiding generic results and to make it feel like service deliverables, not generated, automatic functions. The ugly? The noise. Since we launched, more than a dozen AI tools came out that had grand plans to "design" and showed little delivery. Users will now be more skeptical - and that means we have to work that much harder to earn their trust. But honestly? We don't mind. In the end, consistent quality wins.
AI has entirely changed the way I develop and grow education technology. When I was originally designing coding curriculum, it would take weeks to manually analyze and create custom learning paths. Today AI can analyze thousands of student interactions in real-time and figure out what is the specific problem area with binary trees or dynamic programming. The productivity increases are mind blowing. I have a 70% increase in the speed of prototyping new algorithm explanations and feedback through our AI tutoring system is as good as what I would have provided face-to-face. The students would always say that they experience that they are pair programming with a senior engineer. Yet there is a black side that I did not expect. Nowadays, AI solutions are copy-pasted by many not very talented developers who do not realize the reasoning behind it. I have even interviewed candidates who can talk about complicated algorithms with confidence, and break down when I make them run through their own code by hand. They have gotten addicted to AI crutches. The market saturation is ruthless as well. Three new so-called AI-powered coding platforms are released every week. To stand out, it is necessary to be an innovator, rather than placing ChatGPT on top of the old one. What do I lose sleep over? Graduates who believe they know algorithms on the basis that an AI has taken them through solutions, yet they cannot solve FizzBuzz in a whiteboard interview. The technology is mind-blowing but it is making a generation of developers believe they are ready to work at Google when they are not ready to work at a junior level.
AI changed my life, not just my business. Here's how: The good: AI helped me create an entirely new company, AI Operator, and finally discover what I love. As someone with ADHD, I used to dread certain tasks. Now there's nothing I hate doing, because I can use AI, get it done faster, and even learn something in the process. The bad: Honestly, I don't think there is one, unless you're ignoring it. If AI hasn't impacted your business or career yet, and you're not actively making it happen, that's bad. The ugly: If you keep that fixed mindset and don't start adapting, you're on track to join the millions predicted to lose their jobs in the coming years. White collar or blue collar doesn't matter, it's about mindset. If you've got a growth mindset and you're learning how to make AI work for you now, you'll be fine. If not, well... good luck.
AI hasn't replaced me. It's made me think more strategically, work smarter, and trust my instincts more than ever. Some days are filled with too many to-dos, urgent requests, and not enough hours — clients, campaigns, partnerships, strategy, and the endless details in between. That's where I welcome AI to step in. Not to take over, but to remove friction, cut delays, and eliminate the busywork that used to slow me down. Over the past year, AI has helped me: Speed up analysis that used to take hours (sometimes days) by pulling research, breaking down competitor programs, and surfacing insights to pull together high-level summaries. Turn my messy ideas into structured content — from thought leadership blogs to affiliate program evaluations — without staring at a blank page. Expand my reach by uncovering niche audiences, better prospect lists, and strategic partners without the time sink of manual digging. It's also a sounding board for 'what ifs.' I can test assumptions, debate ideas, and refine them in real time. That's the good. The bad? AI can sound confident, and sometimes it's confidently wrong. Auditing and fact-checking are non-negotiable. It can also become tempting to let my creative muscles rest when they need to stay exercised. Don't prompt on autopilot. Staying deliberate is the only way to keep them strong. The ugly? AI won't fix disengaged teams. It won't spark participation in people who aren't willing. And if you take its first draft and hit publish without making it yours? It shows. Every. Single. Time. That's what I call being "AI lazy." Here's the Truth: AI is like a coach on the sidelines during a game. It can watch the whole field, point out weaknesses in performance from both teams, suggest plays, and highlight missed opportunities. But when the ball's in your hands, the split-second decisions, the risks, and the instinctive moves, that's still all you. AI gives guidance and insight, but the judgment, creativity, and tenacity to win? That's human." AI has prompts, people have instincts. Those instincts, knowing when and why to use AI, refining its output, and giving it context and voice, are still all me. AI amplifies my impact, but I remain central to the process. Enough about me. Explore AI. Don't fear it, embrace it. But never hand over the part of your work that's uniquely you — your voice, your judgment, your instincts, your humanity. The magic isn't in AI, it's in how you use it, and how you play the game.
Founder | Executive Resume Writer | Coach at Kelley Resumes and Wordsmithing
Answered 7 months ago
I'm a professionally certified career strategist who provides coaching and writes resumes. I've seen, first-hand, how AI and misunderstandings about what it can do/how it works keep people unemployed for so long that they actually fall off unemployment rolls. People think that AI resume builders and generic requests to ChatGPT will make them stand out. Unfortunately, the resume builders are usually designed by web and app developers, not people who know how to write resumes, and ChatGPT requires engineered prompts to truly target a resume. Therefore, AI has been incredibly helpful for my business on two fronts. First, many of my clients come to me after being disappointed by AI resume builders and/or ChatGPT. Secondly, I've "cracked the code" to engineering prompts for resumes AND to determining the right keywords for your resume to beat ATS. I'm about to launch a full self-paced program that uses prompts to help people write their own resumes. I know it works because 100% of my test group has gotten jobs or is actively interviewing. Every person in this group had applied to HUNDREDS of jobs with zero interviews and had tried other AI tools. With resume keywords, I've built prompts that accurately analyze postings and determine the keywords that should be in a master-level resume. A second set of prompts precisely tailors the resume to individual postings. Like the pilot group for my self-paced program, clients will come to me who can't get interviews, no matter how many jobs they apply to. In some cases, they've been collecting rejection emails for a year or more. When i give them their new resume, for which I've used these keywording tools, and teach them how to tailor it... they quickly start getting interviews and, ultimately, job offers. Don't hesitate to contact me for more information.
AI has certainly enhanced the way that I handle product strategy and operational effectiveness at Easy Ice. The benefits are obvious: more insight, quicker decisions, and automation, which cuts labor. From forecasting service intervals to optimizing the way we measure product performance in thousands of locations, AI provides us with visibility that we didn't have earlier. It helps us provide a better experience for our customers, with fewer surprises and greater consistency. The worst is that it's simple to get caught up in trusting the technology too much. We've had instances where AI-driven insights got it wrong simply because they weren't able to factor in human subtlety, such as a location's seasonality of demand or urgency of the customer. The ugly manifestation appears when those errors spill into the delivery of services or misdirect field resources. That's when you recall AI as a tool, not a substitute for judgment.
I would say that for me, AI has been a double-edged sword. On one side, it's massively sped up research, brainstorming, content drafts, and even answering email. Things that in the past would take me multiple hours now take only a few minutes. But... it's also super easy to get lazy and rely too heavily on it, which can make your work sound 'meh' if you're not careful enough. In the end, you can't JUST use AI and expect magic, you still need to know your craft.
The use of AI tools has enhanced our PR workflow but the real benefit is when we customize the AI tools to use our own historical campaign data rather than using generic models. Inputting the previous interactions with media, pitch results and journalist preferences using AI produces outputs that are much more appropriate in tone, timeline and audience consideration. It will help us to recreate the strategies that worked well and prevent repeating the mistakes, which will lead to a significant rise in the acceptance rates of the pitches in the competitive industry such as blockchain. It is a time-consuming process, but the accuracy that it provides is beyond comparison. A silent pitfall is that AI may reuse phrase structure found in publicly-available datasets, resulting in pitches that sound like other ones in the market. To address this, all AI-made drafts are put through a bespoke comparison system which indicates overused phrases and structure repetition. This added signature makes our messaging stand out in an email that can be filled up so easily, safeguarding brand voice and making our chances of meaningful interaction with a journalist high.
AI has improved our process speed. We now manage content operations with greater efficiency and use predictive data to support our planning. This contributed to our business growth. However, as content volume increased not all of it delivered real value. We had to raise our content standards and remind contributors that their voice, perspective and expertise are still essential. AI supports grammar, structure and research but does not think like a human. It cannot fully understand what a reader truly needs. For that reason we view AI as an assistant rather than a replacement. Meaningful learning and engagement happen when people lead the process and AI plays a supporting role. Human insight still drives results.
AI tools have improved our operations. They help organize large data sets, merge inventory details, and forecast resale timelines. Teams used to take hours to complete these tasks, but now they happen much faster. This has allowed our team to focus more on decision-making and less on manual work. In that way, AI has added real value to daily processes. However, we have also seen where AI can cause problems. In one case, it misread labeling terms and misclassified medical devices, causing delays during customs checks. This reminded us that AI must be trained carefully for complex industries like healthcare. These tools often miss important details. AI works best when guided by experts who understand the full picture.
AI tools are ultimately the reason for the existence of my company. I created AI detection software a few years ago, when it first became clear that generative AI was going to start becoming a huge thing. With the emergence of ChatGPT into the public sphere, I knew right away that people were going to need to be able to detect AI usage, so I created a solution to a new problem that was emerging.
Honestly, AI tools have largely made things more complicated. There are certain tools that have helped, but overall I think the pressure of AI adoption has presented some challenges. We know that we have to adopt AI to stay competitive and accept the changes in the business world, but we also know that there are a lot of imperfections and risks with AI - legal concerns, ethical concerns, workflow hiccups, general adoption issues. We are constantly trying to find that fine line, and that's often quite challenging.
It has helped to make internal processes more efficient in that we're able to assess AI opportunities based on smaller recurring tasks, and use internal data to get the most out of very specific tools or products. We find this is a much better approach than simply trying to shoehorn a certain AI software or offering into tasks that don't actually require AI or benefit from its usage.
It has meant that we're able to better optimise internal processes in a way that we hadn't been able to previously, without also having to shift overall task reliance to AI. The growth of AI systems means that we can pick and choose the best ones based on context and individual requirements.
I've been implementing AI across newsrooms since my CMO days at the LA Times and now as CEO of Nota, so I've seen this change from both sides - as a media executive trying to save costs and as someone building the AI tools that promise to help. **The good:** AI has genuinely revolutionized content workflows for our media partners. We're seeing 92% reduction in newsletter creation time and 37% boost in social volume at major outlets. One client increased pageviews by 21% simply by using AI to optimize their existing stories for different platforms - same content, better distribution. **The bad:** The integration headaches are real and expensive. Most newsrooms have legacy systems that don't play nice with AI tools, so you end up spending months on technical debt before seeing any benefits. We've had clients spend more on integration consulting than they saved in the first year. **The ugly:** AI is accelerating the local news crisis in ways people don't talk about. Smaller outlets are using AI to cut editorial staff, thinking technology can replace journalism expertise. I'm watching newsrooms produce more content with fewer humans, but losing the community connections and source relationships that actually drive subscriptions and trust.
After 15 years in SEO and running SiteRank, AI has completely transformed how we deliver results for clients. I'm uniquely positioned here since I've implemented AI across content creation, analytics, and client workflows while maintaining the human strategic oversight that makes or breaks campaigns. **The good:** AI has boostd our content production and keyword research capabilities beyond anything I experienced at HP or previous hosting companies. We're now generating months of optimized content in days, and our AI analytics platforms helped one client increase engagement by 340% by identifying search patterns we never could have spotted manually. The productivity gains let us take on more clients without sacrificing quality. **The bad:** AI-generated content without human oversight creates generic fluff that Google increasingly penalizes. We learned this when early AI content experiments actually hurt some client rankings because the content lacked the depth and expertise signals search engines now prioritize. You still need someone who understands SEO fundamentals to guide the AI effectively. **The ugly:** The market is flooded with "AI SEO experts" who are basically just ChatGPT resellers charging premium prices. I'm seeing businesses get burned by agencies promising instant results with AI magic, then delivering cookie-cutter strategies that ignore basic optimization principles. It's making legitimate AI-improved SEO work harder to sell because clients are becoming skeptical of any AI involvement.
I've been using AI to completely transform nonprofit fundraising since launching KNDR, and the results have been wild in every direction. **The Good:** AI donor prediction changed everything for our clients. We built a system that analyzes giving patterns and predicts when donors are most likely to give again, which helped one nonprofit client jump from 200 monthly donations to over 1,000 in just two months. The AI handles all the timing and personalization while our team focuses on strategy. **The Bad:** AI-generated fundraising copy almost killed a major campaign last year. The tool created emotionally manipulative content that completely missed our client's authentic voice, making their supporters feel like they were being scammed. We caught it before launch, but it taught me that AI doesn't understand the delicate trust relationship between nonprofits and their communities. **The Ugly:** AI automation created donor fatigue we didn't see coming. One client's AI system got too aggressive with follow-ups, sending perfectly timed but overly frequent touchpoints that actually decreased donations by 30% over three months. Donors started unsubscribing because they felt like they were talking to a robot, which they basically were.
After 12 years running tekRESCUE and speaking to 1000+ business leaders annually about AI implementation, I've seen both the breakthrough moments and the costly mistakes firsthand. **The good:** AI has revolutionized our cybersecurity threat detection capabilities. We're now catching potential breaches 75% faster than traditional monitoring, and our AI-powered predictive maintenance systems help manufacturing clients like those using General Electric's approach reduce downtime by identifying equipment issues before they cause production stops. Our clients save thousands in prevented cyber incidents monthly. **The bad:** The human element became more critical, not less. Early on, we let AI handle too much of our initial client consultations and lost three major accounts because the technology missed nuanced security concerns that required human expertise to identify. You can't automate relationship building or the strategic thinking that comes from years of cybersecurity experience. **The ugly:** AI created a false sense of security for many businesses. I'm constantly cleaning up after companies who thought an AI cybersecurity tool meant they could fire their IT staff, only to get breached because nobody understood how to properly configure or monitor the systems. The most dangerous phrase I hear is "the AI will handle it" - that's when vulnerabilities multiply.
Running digital campaigns with $20K-$5M budgets for 15+ years, I've watched AI completely reshape how we approach paid media optimization and client reporting at Multitouch Marketing. **The Good:** AI-powered bidding strategies in Google Ads have boosted our healthcare clients' conversion rates by 35% while cutting cost-per-acquisition in half. What used to require manual bid adjustments every few hours now happens automatically, and our campaign performance data shows consistently better results than our old manual optimization methods. **The Bad:** AI tools have made our clients dangerously overconfident about campaign setup. I'm constantly fixing accounts where business owners used AI to "optimize" their Google Tag Manager configurations, creating tracking disasters that took weeks to untangle. One e-commerce client lost $15K in ad spend because an AI tool suggested keyword bids that were completely wrong for their market. **The Ugly:** AI-generated ad copy sounds increasingly robotic, and our conversion data proves it. Despite AI promising "personalized" ad content, we're seeing 20% lower click-through rates on AI-written ads compared to human-created copy for our higher education and non-profit clients. The irony is that in trying to optimize everything, AI often removes the human elements that actually drive conversions.
Running a digital agency that's managed $100M+ in ad spend, AI has completely transformed how we operate - but not always in ways I expected when we started integrating these tools in 2022. **The good:** AI has made our keyword research and ad copy generation about 10x faster. What used to take our team 8 hours of manual work now happens in 45 minutes, and we're finding keyword opportunities we would have missed entirely. For that personal injury law firm I mentioned that saw 1,200% organic traffic growth - AI helped us identify long-tail legal queries that their competitors completely overlooked. **The bad:** Early on, I got burned trusting AI too much with client strategy. We let an AI tool recommend budget allocations for a $50K/month Google Ads client, and it completely misread seasonal trends in their industry. Cost us three weeks of poor performance before we caught it. Now we use AI as a research assistant, never as the decision maker. **The ugly:** The biggest challenge is client education. Everyone thinks AI means instant magic results, so they expect campaign optimizations that used to take 90 days to now happen in 2 weeks. I spend way too much time explaining that while AI speeds up analysis, market dynamics and user behavior still need time to shift. It's created unrealistic timeline expectations across the board.