How agentic AI could transform travel
How agentic AI could transform travel
https://www.mckinsey.com/industries/travel/our-insights/how-agentic-ai-could-transform-travel?
Jules Seeley is a senior partner in McKinsey’s Boston office. Lucia Rahilly is the global editorial director and deputy publisher of McKinsey Global Publishing and is based in the New York office, and Roberta Fusaro is an editorial director in the Boston office.
AI agents could take the friction out of travel logistics—and reshape how customers plan, purchase, and experience their trips.
Yes, dreaming up your next getaway can be exhilarating. But booking it? Often less so. For many customers, the thrill of travel risks getting lost in logistics, says McKinsey Senior Partner Jules Seeley. On this episode of The McKinsey Podcast, he joins Global Editorial Director Lucia Rahilly to discuss new research on the rise of AI in the travel industry, including the advent of AI agents that could design end-to-end itineraries, rebook disrupted flights, and tailor recommendations to each traveler’s tastes—changing the calculus for customers and travel employees alike.
The McKinsey Podcast is cohosted by Lucia Rahilly and Roberta Fusaro.
The following transcript has been edited for clarity and length.
Travel in the age of AI
Lucia Rahilly: ‘Tis the season for holiday travel, and for some of us, that means confronting a slew of logistical decisions: deciphering carry-on fees, deliberating over cost vs. convenience trade-offs, deciding whether to splurge for a seat upgrade. McKinsey Senior Partner Jules Seeley says these practical to-dos sometimes diminish the delight that travel otherwise inspires.
Jules Seeley: The typical customer says they like the travel research experience. They like to explore and think about where they want to go. But they don’t enjoy the practical side of converting that into a specific trip itinerary.
Lucia Rahilly: Agentic AI just might be the travel assistant customers have been looking for.
Jules Seeley: We’re excited about agentic because over time, it could be a very different way to manage travel that lets customers focus more on the excitement and not as much on the friction and pain.
Lucia Rahilly: So when it comes to travel companies, what’s the state of AI adoption?
Jules Seeley: We’re seeing significant adoption already, particularly in internal experimentation—travel companies using it to help improve their own business.
Lucia Rahilly: And have companies using AI seen heartening results, or is that still TBD?
Jules Seeley: I would say it’s still TBD. There’s a bit of the AI paradox, where we see about 80 percent of companies actively using AI in some form but only 20 percent saying they can see any direct impact, particularly in the P&L [profit and loss] of the business. That reflects the early stage we’re at with AI. We’re confident that over time, we’ll see the impact flow through both to the economics and to the customer experience.
Humans and agents at work—together
Lucia Rahilly: You’ve said that the most significant area of adoption has been internal. Suppose I’m a frontline travel worker. How could AI affect what I do and how I do it?
Jules Seeley: Across a whole set of roles within travel companies, AI helps employees become more efficient by doing more of their manual work and freeing up time for the added value they can bring. We think that’s an early path to adoption and one that there’s quite a lot of excitement around.
In addition, there’s the other side of AI: In automating many tasks, it might also change the employee landscape. To that point, our research indicates that skill sets might need to change, but that over time, these evolutions will help organizations because employees will be freed up from managing systems and more able to deliver meaningful service.
Lucia Rahilly: Let’s say agentic becomes capable of managing some processes from end to end. What kind of human-only skills will remain vital to the travel experience?
Jules Seeley: Travel is a very personal and emotional area; customers are looking for an experience that inspires and excites them. Even when they have to travel—for work, for example—people look for what we call the magic of the travel experience. That means there’s always a role for people and physical touchpoints to help make sure customers are getting the best from that experience.
Lucia Rahilly: Walk us through the kinds of operational processes our research suggests might be largely or even fully delegated to agentic AI within the next few years.
Jules Seeley: These areas include marketing and how you think about targeting your marketing; some elements of customer service featuring AI chatbots, AI interaction through a website, and even AI digital voice engagement; and broader sales activity, sales origination, and sales operational support. AI can code on behalf of an organization as well. It’s supporting more and more internal activities, automating some parts of them and making them even better and more powerful.
Making headway on the agentic journey
Lucia Rahilly: Suppose I’m a travel leader, and I’m sold on the benefits of investing in agentic. What’s the right starting point?
Jules Seeley: One is internal processes because organizations have visibility and control over them. They can make changes that are less visible to external stakeholders, which gives them a bit of a canvas to experiment on without getting tripped up by external challenges with third parties. It also can drive meaningful cost efficiency opportunities over time, which in lower-margin businesses can be an attractive part of AI deployment. Something has to help fund the technology that goes into making these changes.
One caveat: While those are very valuable capabilities, it’s not clear that being agentic AI enabled in your HR or finance processes or in a call center is going to provide long-term strategic advantage. We’d expect many companies to similarly enable their internal processes with AI.
In addition, we encourage leaders to look at their company and think clearly about what they want to be known for. What’s the magic of their organization? How do they think about AI’s role in that part of the organization? If that’s what gives them a competitive advantage, AI could play a big part in making it as amazing as possible.
Lucia Rahilly: Does the travel workforce have the skills necessary to adopt agentic at scale? Does piloting agentic internally help develop these skills, or do leaders need to put formal upskilling programs in place?
Jules Seeley: In general, I’d say none of us has the deep capabilities today to harness the full power of agentic. Nor do we really know where it’s going. It’s a learning journey for all of us, and we should experiment both at work and in our personal lives. Are you using agentic to explore your own travel journeys? To shop? To research topics or synthesize materials, inside and outside of work? Encourage your team, from top to bottom, to learn about agentic AI and what it can do.
We also encourage formal learning journeys. We often go on these with our clients. We run some executive immersion sessions where for two or three days, we’ll have the entire executive team or board immerse with us and other organizations to really get a flavor for what the technology can do. Then over the next six to 12 months, they explore how those cutting-edge capabilities can become more present in their own organization.
Lucia Rahilly: Learning takes time, and internal experimentation takes capacity. Is our belief that the efficiency benefits of agentic AI are immediate enough to help bridge that capacity gap?
Jules Seeley: Part of that is prioritizing or reprioritizing current activities. Many efforts happening in organizations might now be less important because of agentic opportunities. We encourage organizations to look through their roster and decide whether all their efforts still have the ROI they expected, given the newer agentic capabilities. We also encourage reprioritization to ensure there’s enough capacity and bandwidth, both technical and managerial, for agentic opportunities.
Managing risks—and reluctance
Lucia Rahilly: How should companies introduce agentic to customers who might err on the side of reluctance? Are there some interactions that might enable a wade-in-the-water approach?
Jules Seeley: There are ways to experiment without the commitment hurdle of having an LLM [large language model] plan and book an entire trip. For example, imagine customers starting on a journey of physical purchases, perhaps of smaller commitment levels, and then getting more comfortable with committing larger dollars and with the complexity travel involves.
And while an LLM is never perfect, there will come a point when it’s as good as the customer, who also doesn’t know anything about that particular hotel in that particular region or about the choices of airlines or activities. So travelers will put some trust in the thousands of other travelers who’ve been on that journey and the LLMs’ ability to synthesize that and create something for them.
Lucia Rahilly: Are there governance or oversight mechanisms that should be in place for travel companies, given that customers’ money and personal logistics are on the line?
Jules Seeley: There are a few elements travel companies will have to think about. First, it likely becomes less transparent who the ultimate booker of the travel is. If I’m using my favorite LLM to research a trip to Paris, it’s not clear whether the LLM is using the airline website, the hotel website, or if it’s intermediated through an online travel agency [OTA] or perhaps even buying a package behind the scenes from a package travel provider.
That may create questions for customers, as well as differing risks for providers depending on whether they are the merchant of record, the transacting party, or an intermediary along the way. With that are many elements of payments, like currency and exchange rates, and whether customers’ money is held securely if their trip is refundable. It will take some time for either the norms or, in some places, the regulations and rules to account for this level of complexity.
Lucia Rahilly: Forgive me for bringing catastrophic thinking into the mix, but suppose there were some kind of agent-related imbroglio that affected a lot of customers. Do leaders need to do anything specific to prepare for larger-scale logistical or reputational risk?
Jules Seeley: When agentic means that I, as the customer, have not chosen exactly which pathway is being booked and who my counterparty is, it begets questions: Do the individual companies involved in that research process that ultimate transaction? Are they clearly aware of the risks and issues they have to manage?
There are a lot of questions about the ethical use of AI and how pricing works. There’s a lot of sensitivity around AI and personalized pricing, for example. There’s a lot of risks when it comes to sending intellectual property, as well as personal and financial data, through the chain. What will be really important is making sure risk management processes are fully up to date.
What agentic AI means for brands
Lucia Rahilly: Suppose travelers start interacting primarily through AI agents. Will brands need to start thinking differently about the way they maintain relevance and loyalty? And should leaders be thinking about that now?
Jules Seeley: LLMs could provide an incredible amount of detailed nuance and tailored information without a brand’s stamp. This does raise the question: What is the future value and relevance of a brand, and how do you keep that deeply connected to customers? Our sense is that brands that have a powerful, clear value proposition will continue to have that connection because customers will seek it out. For example, customers may say, “This is the city I want to stay in.” But then they could also say, “and these are the brands I like.” Or the LLM may already be aware of the brands they like. Brands that are weak or lack differentiation are likely to suffer more in the future.
Lucia Rahilly: Is there a way for smaller travel players to get some of the benefits of AI or participate in the AI-enabled ecosystem without being left behind?
Jules Seeley: In an agentic world, where there’s a large availability of information about different experiences, you could imagine an LLM would start to surface those that resonate with like-minded consumers—which could create a higher level of visibility for some boutique brands or boutique experiences that haven’t been as visible in the past.
On the flip side, it’s likely to be harder for those organizations to develop the sophistication to participate as actively as larger organizations can. That’s where large organizations will still have some of their edge—their ability to understand where the customer is and what their expectations are and then to adapt their own businesses accordingly.
Travel in an agentic future
Lucia Rahilly: Say more about a world where there are an increasing number of agents participating in travel through LLMs, but also bespoke agents through individual companies.
Jules Seeley: A hotel brand or an airline or a cruise or an OTA will likely have its own agents you can interact with and develop its own vertical expertise on how to use agentic in travel, in addition to the horizontal expertise of the LLMs. That’s some of the debate going on right now—the extent to which travel will end up as a vertical agent, given depth of experience and complexity, or whether the horizontal LLMs will play a bigger role due to their broader wealth of information about customers.
Lucia Rahilly: If we fast-forward, say, three to five years, what do you think would be most surprising about our experience of travel in an agentic-enabled future?
Jules Seeley: We’ll likely see a few meaningful shifts. First is this overall experience of travel research and travel booking. We’ll likely see more passion and emotion and less frustration around that booking experience.
Second, we’ll see the leading travel players focus on a small subset of areas where agentic capabilities will make the most difference. What are those domains, and how do you completely reengineer them? I’d say we’re still in a world where AI is being applied to steps in a process or steps on a journey. As the capability becomes more mature, we’ll see that entire process or journey getting reengineered from end to end.
Third, there is a lot of research now on voice assist and voice engagement. To date, it hasn’t been as helpful for travel beyond trip research. Once you get past the description of a particular destination, using a voice assistant to list 50 hotel choices is very inconvenient. You still want to display the product. One of the things we may see, though more complicated, is the ability to personalize to the individual customer—based on the data, the insight, the information, and the LLMs’ processing capability—to narrow that list down. Suppose an LLM can find you a hotel, or a choice of three hotels, that really resonates with what you’re looking for in terms of price point, experience, location, and amenities. That would significantly change how you interact with a travel company and become much more like a rich conversation and much less like an index and database search.
The AI reckoning: How boards can evolve
https://www.mckinsey.com/capabilities/mckinsey-technology/our-insights/the-ai-reckoning-how-boards-can-evolve
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How can boards best help guide companies through the competitive dynamics unleashed by AI?
Artificial intelligence—including its many offspring, from machine learning models to AI agents—is much more than the latest wave of technology. It is a general-purpose capability that is poised to touch almost every sector, function, and role, with the power to reshape how companies compete, operate, and grow. With trillions of dollars potentially at play and implications that could be existential to companies, AI is closer to a reckoning than a trend. And that is why AI is a board-level priority.
More than 88 percent of organizations report using AI in at least one business function; however, board governance has not matched that pace. While interest in AI seems to have spiked after the introduction of ChatGPT, as of 2024, only 39 percent of Fortune 100 companies disclosed any form of board oversight of AI—whether through a committee, a director with AI expertise, or an ethics board.
Even more telling, a global survey of directors found that 66 percent report their boards have “limited to no knowledge or experience” with AI, and nearly one in three say AI does not even appear on their agendas.
Having a low rate of AI adoption by boards might seem obvious at first, given the often-sizable investments many companies have already made in AI and the limited returns to date. AI adoption has not yet led to significantly improved performance for most businesses, with companies reporting modest levels of savings and new revenue.
In our experience, however, many of the issues plaguing AI programs—such as a lack of strategic coherence and unclear value dynamics—are precisely the ones that boards are best positioned to address. In other words, boards have an important role to play in redressing the disappointing outcomes.
That role is grounded in developing a strong understanding of how AI can change the business, both for better and for worse. Boards, therefore, need to become fluent in AI, not necessarily as a technology, but as a catalyst that affects the competitive dynamics of their sector. This might mean, for example, understanding how general-purpose AI systems can undermine a specific product line or service or how an AI-powered capability creates an opportunity to expand into a new market or adjacency.
AI-savvy boards will be able to help their companies navigate these risks and opportunities. According to a 2025 MIT study, organizations with digitally and AI-savvy boards outperform their peers by 10.9 percentage points in return on equity, while those without are 3.8 percent below their industry average.
What boards should do, however, is the bigger question—and the focus of this article. The intensity of the board’s role will depend on the extent to which AI is likely to affect the business and its competitive dynamics and the resulting risks and opportunities. Those competitive dynamics should shape the company’s AI posture and the board’s governance stance.
To better understand how boards can evolve to address AI, we conducted interviews with directors from 75 boards across various industries and geographies. We also analyzed the findings from the McKinsey Global Survey on the state of AI and its data sets, which cover thousands of executives globally.6
This analysis highlights two priorities for boards:
- Defining the company’s posture toward AI adoption. Most organizations still lack a clear view of how AI fits into their strategy or transformation agenda. Without alignment between the board and management, oversight becomes either superficial or paralyzing.
- Tailoring the governance model to match the company’s AI posture. The board’s task is to calibrate its role around where to engage, what to oversee, and the cadence to use.
This article will explore how boards can address these two priorities and also lay out six governance actions that every board should consider.
Defining the business’s AI posture
A business’s AI posture clarifies how AI fits into the company’s strategic ambition and its priorities. Not every enterprise will approach AI the same way, nor should it. But having clarity about the potential impact of AI on the business provides boards and management with a foundation for making key strategic, governance, and investment decisions.
Two strategic dimensions determine a company’s approach to AI, with where companies fall along the spectrum of each defining their posture:
- Source of value. Will AI help the company move beyond its core business model into new products, experiences, and revenue streams (expand strategically), or will its value primarily come from improving the existing model (optimize internally)?
- Degree of adoption. Will AI be embedded across the enterprise (holistic) or applied in targeted use cases (selective)?
A company’s position along these dimensions determines its AI posture (exhibit). Determining which archetype a company wants to pursue is less about precision and more about aspiration. Companies are unlikely to fit neatly into one archetype and may straddle multiple ones—particularly at scale, where different business units or functions may pursue different approaches.
What matters is that the board aligns on the business’s aspirational strategy using a clear view of the opportunities and risks so that it can tailor the governance approach. As the business gains greater experience with AI, the board can modify its posture.
The four archetypes are as follows:
- Business pioneers. AI sits at the center of strategy, driving new offerings and redefining competition. Think of a medical-device company that could evolve from selling equipment to delivering AI systems that interpret scans and suggest appropriate treatments, thereby transforming from a manufacturer into a healthcare solutions provider.
- Internal transformers. AI becomes the backbone of operations, reshaping how an enterprise runs. An example of this archetype is a mining company deploying AI to guide exploration, automate extraction, and optimize refining—thereby transforming a labor- and asset-intensive model into a data-driven one. Similarly, a media studio could embed AI across its production pipeline, producing faster, cheaper content at scale.
- Functional reinventors. AI is used to enhance specific workflows with proven returns. Companies treat AI as a disciplined, ROI-driven investment rather than a reinvention lever. As an illustrative example, a healthcare system might adopt different AI scheduling, transcription, and workforce tools. Or a logistics provider could use route optimization and predictive maintenance to cut costs.
- Pragmatic adopters. AI is adopted for targeted applications based on already proven market traction. This is essentially a fast-follower approach. For example, a consumer goods company may wait until off-the-shelf e-commerce recommendation tools have been proved before adopting them to expand to new segments. Similarly, a fashion retailer might start leveraging AI to offer clothing rentals and personalized styling only after others in the industry have proved its effectiveness.
What matters is that the board aligns on the business’s aspirational strategy using a clear view of the opportunities and risks so that it can tailor the governance approach. As the business gains greater experience with AI, the board can modify its posture.
Tailoring oversight to support the AI posture
Once a company’s AI posture is clear, the board’s task is to calibrate its role to match the business’s aspiration. What is essential for a pioneer moving into new markets will differ from what matters to a pragmatic implementer watching competitors.
To receive a version of this article with a detailed view of the board activities for each archetype, please contact us.
Business pioneers
When AI is the engine of growth, the board’s role is to ensure that executive leadership understands AI’s value potential and how to capture it. This foundation enables the board to collaborate with and provide direction to management to make informed strategic investments and assess whether it possesses the necessary leadership, capabilities, talent, and capital to deliver.
Directors should focus on determining whether management has the entrepreneurial experience, technological know-how, and transformational leadership experience to run an AI-driven business. The board’s role is particularly important in scrutinizing the sustainability of these ventures—including required skills, implications on the traditional business, and energy consumption—while having a clear view of the range of risks to address, such as data privacy, cybersecurity, the global regulatory environment, and intellectual property (IP).
This level of intervention will require a sufficient number of board members with product and broader AI experience, so they can act as thought partners and credible challengers to management.
Example: A global logistics company leveraged decades of trade data to develop a new AI-driven intelligence platform, transitioning from being a shipping provider to an information business. Support for the venture increased after the board validated defensible data moats, stable model performance under drift, and sustainable compute cost.
Boardroom test questions include the following:
- Which competitive advantages does AI enhance or threaten?
- Does our AI business case target a large enough value pool to reshape our market?
- What key resources are needed to do that, and do we currently have them?
- Do we have dedicated people who can manage the environmental, regulatory, legal, and reputational risks that come with being a business pioneer?
- How do we need to evolve our innovation pipeline to match the pace of technological change?
Internal transformers
For companies with the ambition to embed AI across their operations, the board’s role is to direct and oversee the rewiring of the operating model at scale. While all archetypes involve some operating-model changes, internal transformers stretch this across multiple functions in the enterprise—a uniquely complex challenge.
Boards play an important role in challenging management to certify that operational gains are structural rather than temporary and that they meaningfully improve the business’s productivity. This focus requires detailed knowledge of systems and dependencies, as well as the technological foundations (particularly enterprise architecture) that enable cross-functional process modernization.
Boards will need to be particularly diligent in probing resilience, observability, and explainability to certify that systems are stable, trackable, and quickly corrected as needed. The board’s task is to encourage management to balance ambition with adoption, making sure that the organization has a robust upskilling program and incentives aligned to the changes needed on the front line.
Example: One global manufacturer’s board questioned management about whether AI-driven planning, supply chain, and maintenance systems were interoperable and stress-tested before approving new capital. This helped ensure that the AI initiatives were resilient and could scale.
Boardroom test questions include the following:
- Is AI truly rewiring how this company operates or just automating isolated tasks?
- What evidence supports that the operational changes are both structural and sustainable?
- How confident is the management team that it can track and understand how AI is driving cross-functional processes?
- How should we shift our buy-versus-build approach to solidify our competitive advantage and our strategic flexibility?
Functional reinventors
For companies embedding AI into selective workflows, the board’s role is to focus on scaling for value, securing coherence across initiatives, and mitigating vendor-related risks. Board committees in specific areas, such as audit, risk, and talent, play a stronger role in driving AI workflow transformations within their respective domains.
Boards are focused less on the individual workflow modernization efforts and more on supporting management in allocating resources effectively, coordinating dependencies and governance issues across workflows, and determining which investments have the greatest application to a broad range of workflows (for example, developing data products that serve multiple workflows). Real-time dashboards can help boards track outcomes and progress.
Functional reinventors are more likely to buy than build, given the generally narrow focus on workflows. “Vendor lock-in” isn’t a new concern, but boards can play a critical role by probing management to explain how competitive advantage is being protected and to what degree it is being ceded to vendors. Some vendor decisions have long-term implications, such as maintaining internal support capabilities, which management should clarify.
Example: One regional healthcare system’s board now asks its CEO to present a consolidated map of all AI pilots each quarter, covering scheduling, transcription, and workforce tools. The board uses this review to challenge whether pilots are scaling effectively and whether weak pilots are being defunded quickly enough.
Boardroom test questions include the following:
- Which high-value workflows can most benefit from AI?
- How does management set the parameters to manage the risk posed by AI programs in specific workflows?
- What are the advantages and risks of buying versus building core capabilities?
- What is the mechanism for tracking and scaling the most promising workflow programs?
Pragmatic adopters
Boards of organizations that adopt a pragmatic approach toward AI should concentrate on strategic readiness and the risk of inaction. Board members can be most helpful by asking management to share and discuss market intelligence, including competitor moves, market shifts, and AI evolutions.
During these reviews, board members should be ready to constructively challenge management to clarify if and how these developments could threaten the business’s long-term competitiveness and enhance any aspects of the current business model. Boards can establish clear metrics and escalation procedures to track the maturity of relevant AI capabilities deployed by potential competitors, as well as conduct readiness assessments to ensure that the company has sufficient foundations and capabilities to move quickly when an AI opportunity presents itself.
Example: One energy company’s board devotes a portion of its annual strategy retreat to reviewing case studies of AI adoption from adjacent industries. Directors ask management to map the elements, including vendor partnership, capital allocation, and workforce readiness, it would require to catch up quickly if needed.
Boardroom test questions include the following:
- How are we tracking AI developments inside the industry, as well as with competitors, to determine what actions we should take?
- Do we have a credible plan to follow fast on a proven AI capability, and how do we assess our readiness to move?
- What are the risks associated with not pivoting in time in various business areas?
Six actions to take
Our research highlights six actions that boards should consider taking, with the degree of pursuit varying per their AI posture:
1- Align on AI posture and review it annually (at least). The first order of business is to align on what posture the business should take with AI—without that clarity, none of the other actions matter. Boards should then regularly revisit their AI posture in response to changes in the competitive, regulatory, and technological environments. Proactive posture reviews make sure that the company’s stance reflects today’s realities rather than yesterday’s assumptions. This annual review shouldn’t replace more frequent engagement on the topic.
2- Clarify ownership of AI oversight—within both the board and management. Oversight fails without clear accountability. Boards should explicitly define which topics should be reviewed and fully discussed in full-board sessions (for example, material investments to scale enterprise-wide AI), which belong in committees (for example, risk frameworks and material vendor reviews), and which do not require significant board discussion (such as regular operational decisions). Without this specificity, ambiguity emerges and accountability breaks down, or precious agenda time is wasted.
3- Codify a framework for AI governance policy. Most companies draft principles or ethics statements, but fewer than 25 percent of companies have board-approved, structured AI policies. A credible governance framework should specify the following:
- scaling rules (when pilots earn capital to scale enterprise-wide)
- risk thresholds (where human sign-off is necessary and what guardrails should be in place)
- vendor or data guardrails (IP protections, third-party audit rights, security, and lineage standards)
- escalation triggers (what incidents reach the board and how fast)
4- Engage more broadly (and frequently) with those doing the work. It is not enough to engage only with CEOs or CFOs on AI developments in the business. Board directors should be regularly exposed to and interact directly with the executives who are embedding AI into operations (such as chief data and analytics officers and business and division leaders) to gain a deeper understanding of progress against goals and impact on competitive dynamics.
5- Tie AI investment to business value. Boards should encourage management to not only identify but also quantify the potential opportunities and risks associated with AI adoption. This view can help boards guide businesses through the short- and long-term trade-offs that balance opportunity and risk, using their AI posture. Effectively providing that guidance requires solid reporting, but only about 15 percent of boards currently receive AI-related metrics.8 Boards should have access to impact measures such as ROI by business unit, percentage of processes that are AI enabled, resilience indicators (such as override rates and backup drill results), workforce-reskilling progress, and regulatory alignment. This information helps reframe AI strategic direction and oversight in a similar way to capital allocation and risk reviews.
6- Build AI fluency. Directors do not need to be data scientists or deep-tech experts, but they do need to have a sufficient understanding of how AI works and its role in creating opportunities and risks for the business. Building up that base of knowledge happens through ongoing education, regular briefings, external trainings, advisory panels, and input from external experts on emerging technologies, regulations, and risks. Board members should become comfortable with AI by using it in their personal lives, to prepare for meetings, to review publicly available information, and to run analyses on proprietary information only in ways approved by the general counsel.
As boards consider what steps to take, they might consider some of the operating practices for venture capital and private equity companies. Those companies typically have a clearer view and focus on the value opportunities with AI, stronger accountability measures, and a faster operating metabolism, such as with funding decisions.
Ace Brooklyn owners secure $112.5M refi
A pair of New York City-based companies secured the loan to refinance the full-service hotel in the New York City area.
Two New York City-based companies have secured a $112.5 million loan to refinance the Ace Hotel Brooklyn. (Credit: Ace)
https://www.hotelinvestmenttoday.com/Financials/Financing/Ace-Hotel-Brooklyn-owners-secure-112-5-M-refi?
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