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Ryan Kurt posted thisInsurance companies know orders of magnitudes more than frontier AI companies about probabilistic / predictive models that carry legitimate weight & risk in the real world. Where the harm and cost of a wrong prediction is incredibly different than an LLM predicting the wrong next word. They also have much more experience being accountable for the predictions their complex models make. (cough.. like when an LLM 'predicts' wrong and hacks another companies systems and its owner faces no real consequence and is in some ways rewarded) This bit of a paradox makes sense. The insurance industry has a 350 year head start on today's AI industry (only 3K years if you go back to the earliest days of Insurance as concept). I think AI leaders and researchers can learn a ton from Insurance leaders, actuaries, underwriters, service folks etc. This was my main takeaway from the AI Showcase Event I joined along with 65+ Insurance leaders this week. Put on by the The University of Iowa Tippie College of Business and our world class risk management-focused Vaughan Institute. In collaboration with the tech industries most active startup & innovation platform Plug and Play, I was honored to be on an AI panel in my Executive in Residence role alongside Doug Ommen, Iowa's Insurance Commissioner, and Kelly DiCuffa, who leads the human side of AI transformations for KPMG's financial services & insurance practice, with KPMG's Raj Konduru moderating. My other takeaways: - Insurance AI innovation flows through Des Moines & Iowa City. The companies here start with their customers and their business, then work outward to where AI fits Not the other way around - insurers are working on innovative new products to help companies manage the risk of AI agents, and an interesting discussion on the ways AI could mean fewer losses for clients down the road. - GenAI models/tools need to get a lot better at & fit in with Insurance (and other regulated industries) much more than Insurance companies need to 'figure out how to implement AI' better. Implementation is not the main bottleneck. And lack of sophistication certainly isn't. - Huge opportunity for young people inside insurance companies: be the adaptation layer between GenAI & Insurance and vice versa. These are complex, problem-solving entities with decades of intellectual growth and high-paying jobs in the years ahead - This industry is going to lead its own AI transformation in its own way. It will not be reacting to it. - Insurance companies know a lot more about AI than AI companies know about Insurance (not a knock.. makes sense per the above) This makes this center of AI + industry knowledge & collaboration so promising. Thanks to head of the Vaughan Institute, Jim Lewis and my Exec in Residence partner and former Aflac President, Fred Crawford, for pulling me in. And for the opportunity & trust put in me by Tippie's Dean Amy Kristof-Brown & Kang Zhao, Senior Associate Dean
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Ryan Kurt posted thisA flip-phone without internet has been the missing link for me to personally reap large benefits from AI. Counterintuitive but I needed to get as far away as possible from a computer and AI to get the most out of both my Top 'created while walking & talking' deliverables so far have been: - high quality logo &creative designs for a new Sku, - charts/graphs to be included in decks, - website updates, - contract amendment - proposal decks - address complex corporate legal issues-- summarize objectives in meticulous detail to create draft to send to attorney (theoretically reduces turns/ lower fees + optimize protections) - in addition to the mountains of draft Slack, text, and Emails automatically created from my voice (without alternating / changing writing style). *i still write most important internal notes by typing as well as LinkedIn posts & articles. **in each of the above, I translate the idea/ vision in my head in detail so Claude understands what ' great' look like. I find its less mental effort to focus and get my brain to produce the meticulous detail while walking ---- The market is woefully short of specificity around work redesign (other than coding), so here's my little example broken down: - bought Sunbeam flip phone that can text, call or create notes and nothing else - it has top tier voice-to-text (legitimately great - its only 'high-tech' feature) - I walk to/from work most days with the flip-phone (leaving iPhone at office). 40-45 mins each way - on walk in I usually dictate one long note, then text it to my Gmail which links into Claude as a 'markdown file'. Or blue-tooth a txt file to computer (then load into Claude) - Claude translates the .md file into a host of draft deliverables, each sitting inside the correct system for review. i.e. Slack drafts in Slack, emails in Gmail, docs & designs in Google Drive etc. (only one that doesn't work is Texts -- have to copy/paste). - walk home I usually think of a number of things I forgot to close out. so usually more focused on dictating emails, slacks, or texts. - on weekends I usually don't have iphone and by Monday the voice-dictated-note of ideas/ thoughts about work gets pretty long. ----- I'm getting more done faster but that wasn't really the goal. Rather my overall work environment is greatly improved, as is the quality of the output. Once i get this more refined I plan to do a week where I only work from flip phone and only accessing Computer an hour in middle of day. I join calls/ zooms via flip phone already. The challenging link has been getting my updated calendar to appear so I don't miss anything. I may need a different type of 'dumb phone' to accomplish this This won't be for everyone. But for anyone who thinks more clearly, has more energy and creativity when they are away from their iphone/ internet -- and has a role where this type of work is relevant, this type of workflow might be worth piloting.
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Ryan Kurt shared thisI am sensing that sales as a role (and buying) is rapidly shifting and emergent approaches are starting to win in big ways. Trying to dig into the what, why, and how in an essay which has morphed into a long piece on how Sales is changing due to AI (focus is B2B). Some conclusions I am still working through before publishing, but a few I'm certain on. First, the best sellers need a longer horizon view of their performance. Beyond quarters/ current fiscal year & adjust behavior accordingly. Don't optimize for the next deal -- optimize for the total sum of deals over the next few years and create much happier/ more successful buyers, and much higher income for the seller. Second: For purchase decisions with any complexity, buyers fall into two categories. a) Those using AI to help guide market assessment/ decision / negotiation etc. b) and buyers who aren't using AI in that way yet, but will eventually or would if shown how The best sellers will recognize this and adjust accordingly. 1) by de-coupling effort & attention they give their most qualified buyers from the timing of purchase decisions. the job is to Create value all the time, including in ways that are totally separate from the thing you sell and the timing for which it is bought ('the trusted advisor') -connect buyers to other buyers -Share behind the scenes industry trends discussed at conferences, at happy hours (that wouldn't be in AI's training data) -Making intros to people who could be helpful (incld potential clients of your buyer's company) -Drop by for visits to educate them on something in their industry that isn't specific to your product (drew a chart to visualize this one) 2) by showing buyers how to use AI to effectively & objectively assess alternatives, research vendors, etc. Most buyers are going to do this anyway. You can either help them do it better and work with the AI Increasing trust and likely getting closer to the buyer Or don't, be reactive, and operate with less trust and clarity of what a buyer is thinking/ what info they are reviewing 3) when your product/ service is not the obvious best choice for a particular need, tell them. Many will figure that out on their own now. ---- this has a lot of implications. - top sellers will migrate to companies with the best products / solutions even more than before. Because lagging products can no longer hide behind great marketing and sales teams. - some great sellers will end up switching sides and becoming buyers agents. Representing portfolio of companies / execs in their industry and helping them buy the best solution. - classic sellers will often be replaced with Technical / Sales Engineer types who can educate and communicate better in ways that AI can't - sellers must be armed with frontier AI capabilities. Have to assume your buyer is using latest models to assess your market/ product. You must have same (for all the reasons above)
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Ryan Kurt shared thisGEO is a newer acronym / concept that matters a lot to many executives & companies (including many who don’t yet realize it). (GEO= Generative Engine Optimization) So on our next community-wide call on 9/1, we’re going deep on it with senior advisor in The AI Lab community & GEO expert Alex Czurylo and some of his team Right or wrong, much more commerce is being influenced by the words that come out of Claude and ChatGPT. in a growing number of cases in certain industries, AI tools are referencing and recommending lesser-known brands ahead of the established companies. A trend projected to accelerate! Not because small beats big, but because the ranking logic changed and often more nimble companies have adapted faster On the other hand, some industries like finance, healthcare and legal have seen little change to online performance due to AI (why?) And what happens when AI agents handle much more purchase execution in future where the buyers trust is put in the agent to get the right product / solution and much less in the company that made the product or delivered the service. And lastly, the stuff you do to market offline in the “real” world may be even more important than before Hence the need to break it all down and disusss! We will get into it all plus member questions and scenarios. . And back to Alex: He is such a high character leader who loves helping people. Highly confident most attendees will walk away better informed and with things they can do right away to improve their GEO performance. We still have some open spots for execs who want to attend. The Request to Join link in the comments!
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Ryan Kurt shared this"The AI Lab made this possible, but our people did the work and made all this happen. They're the heroes of the story" That's a text from Jessica Cole CEO of Becker's Healthcare, the leading media & live events platform for the healthcare industry. And it's the best summary of what we've learned 15 months into our 'new' business model. We're hitting our first wave of renewals right now (100% so far), which made me think 'maybe our Exec Community + AI Coaching model has product market fit' Maybe? What I am convinced has product market fit are companies taking control of their own AI journeys and resisting the allure of handing the wheel to Forward Deployed Engineers (FDEs) instead, building the confidence and proof of their own abilities, so that when they DO bring in outside help, they can direct it instead of depend on it. Becker's Healthcare is one of the best examples I've seen of doing AI the right way. Certainly the Tops among any PE-backed firm we've seen. Continual progress, month after month Clear, tangible impact and ROI Cost effective and cost controlled Strong culture and buy-in across the team Exceptional leadership from the top Some example 'wins' (most of which happened after we published the case study) One of their Client Success leaders & their COO both built personal AI brains for themselves after guidance from an AI Lab coach. Hours of weekly meeting prep now runs autonomously, prospecting research that took half a day takes minutes, and all their client context is synthesized into real-time account insights That evolved into a "Team AI Brain" for one of their most mission-critical functions. It's given leadership deep transparency into how the team functions and it is taking on more complex tasks as it learns, greatly increasing the capacity of people up to focus on the most important stuff. So many individual leaders and contributors at Beckers have leveled up and are carrying the transformation forward themselves. Too many to list, but special shout-out to Raphael Roxas, Annie S., Daniel Gest, Virginia Egizio, CMP , and Mackenzie Bean! And it starts at the top. Katie Atwood and Jessica Cole lead from the front. a safe environment to experiment and grow, and incentive to innovate. Stay tuned for more case studies in coming weeks! (case study link in comments)
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Ryan Kurt posted thisMost the discussion on AI's impact on workers is backwards. What will AI do to the economy, 'my company', 'my team', 'my role'? to me? Instead of acknowledging the incredible opportunity for workers & students who decide they want to accelerate their careers/ earnings/ lives. Its a true arbitrage moment for those who take it. The economy, almost every company and most teams have yet to figure out how AI can really help them But more and more individuals have and the barrier to entry to become one of those people is low. If you've figured out how to use AI to increase the capacity and/or quality of your individual work product, and you are an early adopter in your org and you think what you've figured out would apply to your broader team or even company Go present the proof to leadership and make the case for a promotion now in exchange for helping others adopt AI (if you are a student with a dream company - email proof of ability to execs at that company. ) Or ask for more pay tied to being able to handle a higher amount of things in future Or consider approaching your leadership with an outcome based deal similar to the ones McKinsey or other consulting firms offer "If I am able to create something (tool, process, training) that increases the capacity and/or quality of the work product for this team by X amount/ percent, by this date, will you give me a bonus of Y? ... and if I don't, then you don't pay me the bonus" Most CEO's I work with would love it if their people brought opportunities like this forward The incentive / comp structure will create discomfort in many places. But this sort of culture is how incumbents avoid being disrupted And how they become the ones doing the disrupting
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Ryan Kurt shared thisTrust in AI is scarce. Not helped by prominent voices many people listen to taking $$ to recommend AI products, models or services companies. (Where this happens explicitly as sponsorship is very different than when people with influence don’t disclose an arrangement) I’ve gotten 2 requests like this in the last few weeks from very well known companies in AI For executives: anyone in AI asking you for money in exchange for somethkng, ask about their business models, incentive structure and any monetary partnerships they do or don’t have
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Ryan Kurt posted thissome thoughts on AI budgeting given its that time of year & its become one of the main topics in our community. - I have strong conviction that the companies who figure out AI best will grow faster via new opportunities they couldn't see/ unlock before (some recent data backs this up). So there's a philosophical argument that companies who feel like they're 'doing AI well' should view much of the expense as a growth lever, even if the return isn't immediate. - But the view from CFO chair still paints a confusing picture. A business line exec asks for more AI budget while also asking for headcount growth at the same rate as before. And doesn't alter their growth forecast up. That math doesn't math. If you're asking for more AI budget, I do think you should be signing up for something. At a minimum, a commitment & plan for how you will investigate new growth opportunities. Ideally, sign up for some amount of: a) higher growth (if not immediate, needs to be there at some point). b) lower cost somewhere else. c) Slower future hiring in some areas (not arguing for displacement, just grounding in the realities of finance) Leaders asking for AI $$ need pick at least one. Each one is ingredient for operating leverage. - the blanket exception, there should be some baseline level of AI spend with no ROI requirement attached. a learning budget. The teams using AI at increasing levels with increasing fluency are likely to find more new opportunities than those without - exception #2 - don't limit your best people's utilization. "the most expensive AI Token is the one your best person is afraid to use" --- Simple to write all that down in a LinkedIn post but hard to do in reality.
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Ryan Kurt posted thisFor motivated individuals, this school year is the best time ever to be an undergrad in business school. Because the AI skillset you can now build in weeks can turn into a massive head start on career when it’s paired with business fundamentals and access to executives, Something business schools already do well. And the ones who seperate on their ability to help students navigate AI will support the playbook below in some form. The playbook: 1) Build the skillset immediately. Learn ABOUT AI and learn to USE AI. Which are Different things. About: the foundations and history, irrespective of any tool. Machine learning, neural nets, transformers, LLMs, probabilistic vs deterministic. What these things are naturally good at, where they naturally struggle. Inherent risks. Use: get proficient in multiple tools (Claude, ChatGPT/Codex, Copilot). Build agents. Build a personal AI brain that works with any of them (knowing how to do something in Claude that also works in Copilot is very useful) 2) build proof of skill immediately Everything you build, and can explain how it works and why it’s valuable, is the start of your portfolio of proof. You can get to a surprisingly high level here in a few weeks max. Schools should provide guidance / curriculum on #1 and #2 but be prepared to facilitate students guiding other students, and for a lot of self guided learning. 3) Do the normal business school stuff. Take it seriously. Learn accounting, finance, sales, ops etc without any/ much help from AI. Foundational business knowledge is more important than ever. It’s what makes your AI ability/ work most useful to a company. 4) Use the asset your school already has. Alumni further along in career. Company leaders. CEOs and CxOs of companies of all sizes, already connected to your school. Lean into it hard. Show these folks what you’ve built. offer to build for them. Or better yet, teach them to do it themselves. Do the same for your parents if they work, aunts/ uncles. Friends parents. Anyone further along in career The stuff you do with/ for others already in economy is the most valuable proof. *Creating many more of these alumni/ local business connections is an area where schools need to rapidly expand and invest. —— Anyone who does the above almost certainly gets a job offer, likely before the end of the year. Senior or not. And the network of connections, possible mentors etc you could gain can stay with you for decades.
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Upendra Belhe PhD exactly. This is a central piece to the how Insurance is set to flourish in my opinion
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Ryan Kurt liked thisRyan Kurt liked thisLast week marked our first McKinsey & Company × OpenAI partnership event. As part of McKinsey & Company’s inaugural American Tech Foundry: AI Accelerator for Federal Leaders, we brought together senior leaders from across the federal civilian, health, and defense communities for a hands-on working session focused on translating the potential of AI into measurable mission impact across acquisition, supply chain, workforce transformation, and improper payments. I am especially grateful to Hartley Caldwell and Megan Crespi for joining us and sharing their perspectives as leaders navigating the challenge of modernizing their organizations to meet their missions. Thank you both for contributing your expertise and helping make our inaugural event such a meaningful one. Thank you to the OpenAI team for your continued commitment to our partnership, and to everyone across the McKinsey and OpenAI teams who helped bring this event to life. This is what a great partnership looks like: bringing together the right people, technology, domain expertise, and innovative ideas to translate the potential of AI into responsible, real-world impact for the public sector.
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Ryan Kurt liked thisRyan Kurt liked thisI recently wrapped up my summer internship at The Ride Platform. I came in as a finance intern, where I got the opportunity to sit in on a variety of meetings, be a part of and take ownership of financial processes, observe board prep, and much more. What I did not expect was everything I got to do outside of my finance role. Over the summer I built a variety of AI powered automations and workflows. These included KPI dashboards, executive assistants, and more, for teams and leaders across the company. It has been great getting to see what I have built being used and making an impact. I would like to thank Morgan Rafferty, MBA for taking me under her wing this summer. Whether it was answering all my questions, pulling me into meetings, or getting me involved in projects, she contributed greatly to my ability to succeed this summer. I would also like to thank Jeff Cavins and Jennifer Young for trusting me with opportunities that allowed me to contribute to the company in a way that I could have never imagined. I am so grateful for my internship experience here, and I am very excited to share that I have officially started full-time as the FP&A AI Specialist! I look forward to continuing to be a part of such a great team and company!
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Ryan Kurt liked thisI can't tell you how excited I am to be partnering with Teri Hatfield again! We had a great run together at Salesforce and Tableau, and now we're bringing the same drive, energy and innovation to Iterable. LFG.Ryan Kurt liked thisToday I'm excited to join Iterable as Chief Revenue Officer. Throughout my career, I've been fortunate to help organizations navigate some of the industry's biggest technology shifts—from digital transformation at Verizon, to changing the way organizations visualize and understand data at Tableau, to helping shape the next generation of AI-powered customer engagement at Salesforce. Each chapter reinforced the same lesson: technology creates new possibilities, but meaningful change happens when people know how to apply it. I've come to believe that great customer relationships don't start with technology. They start with understanding your customers. Trusted customer data creates understanding. Agentic AI makes that understanding actionable. Execution creates exceptional customer experiences. That's what drew me to Iterable. Iterable stood out because it's built around that belief. Helping brands transform trusted customer understanding into intelligent, real-time customer engagement is exactly where I believe marketing is headed. It's exactly the kind of challenge I was hoping to find. I'm especially excited to partner again with Sam Allen. Sam leads with clarity, trusts great people to do great work, makes decisions, and creates a culture of accountability. As he often says, "clarity is kind." It's a leadership philosophy I deeply respect. I'm also excited to join Nick Beil, Priya Gill, Samya D., Andrew Boni, Victor Rago, Vasu Kohli , Carrie Messner, and Jim Bartolomea. Equally compelling is the team behind it. From my very first conversations, I felt a shared vision, an urgency to execute, and a level of trust that's increasingly rare. It's a culture where talented people challenge one another, make decisions, hold each other accountable, and move forward together with a shared commitment to customers and to one another. There are so many talented people I'm looking forward to working with—I'll recognize more of them in the comments below. I'm excited for what's ahead. Let's get to work.
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Ryan Kurt liked thisRyan Kurt liked thisRarely do I disagree with Nathaniel Whittemore, but his recent take on The AI Daily Brief how to handle rogue AI seems really short-sighted to me. "You can't plan for an upheaval that isn't here, isn't inevitable, and isn't one thing." Sure you can. Something as knowable and (sadly) familiar as an earthquake, we can stockpile resources and enlist people to be called up as emergency workers for rescue and recovery. These resources might be 'wasted' in the sense of not being used if the earthquake doesn't happen this year, but better to have them than to need them. Something as unknowable and unfamiliar as rogue AI is more complicated, yes but we don't not plan because of this complexity. We use our imagination, use AI for brainstorming, use old-fashioned software for predictive modeling, put experts together on a committee and make the best plans we can. And it's more necessary to talk about plans BEFORE the rogue AI event happens, because the AI landscape is moving MUCH faster than human institutions and human brains can keep up with. Our plans might be 'wrong' in the sense not not meeting the exact need of the moment, but that shouldn't stop us from trying. The most credit I can give NLW on this point is that many people assume they know exactly what will happen with rogue AI. Making plans based on that certainty can be a risk in itself, blinding us to other possibilities. We don't know what will happen, and many predictions have been proven wrong. (There has not been a massive jobs apocalypse by now, as some predicted.) But that means we need more robust and creative plans, not plans that wait until damage is done to begin planning. #AI #RogueAI #Planning
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Ryan Kurt liked thisRyan Kurt liked thisThroughout history, the insurance industry has adapted to support innovation and economic growth. Today, the space economy represents one of the newest frontiers. Satellite launches. Constellation management. In-orbit collisions. The underwriting frameworks for these risks are being built now, largely by specialty carriers and reinsurers that recognized the opportunity early. As commercial activity in space continues to grow, so too will the need for risk management, creating new challenges and opportunities for our industry. It's one more example of why understanding the space economy is becoming increasingly important for insurance leaders, and one of the many topics we will explore alongside Brian Miske, KPMG US Americas Space Lead during the KPMG US 38th Annual Insurance Industry Conference. Register today: https://lnkd.in/gvWeTm_j #KPMGIIC
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