Analyzing the InterCon Times Square deal
NEW YORK CITY – Three astute investors are betting on the ongoing recovery in New York City as Highgate, Gencom and Argent Ventures have acquired for approximately $230 million the 607-room InterContinental New York Times Square from a joint venture between Tishman Realty and Metlife Investment Management. The deal was backed by a $190 million loan from Monroe Capital.
The deal will also see the property become a franchise with Highgate taking management from IHG.
Gencom, which also acquired the Thompson Central Park last year, stated its first InterContinental-branded hotel will undergo a comprehensive renovation of guestrooms and public spaces. The hotel currently features approximately 20,000 square feet of flexible meeting space, a signature restaurant, a Shake Shack, and a 24-hour fitness center.
The deal was brokered by Eastdil Secured, representing both the seller on the sale and the buyer on securing the financing.
Analyzing the deal, David McCaslin of CapStar Advisors said, “The New York market has strong enough demand characteristics that help drive interest. The combination of being able to project more favorable interest rates, loan expiration pressure and fund life issues is finally allowing a convergence of market pricing to occur. This should signal a bit more robust 2026 deal market.”
The deal, first rumored in September, is the second biggest in the city this year with Kam Sang Company’s $235 million October purchase of the Edition Clocktower Hotel being the biggest.
The InterCon opened in 2010 and was refinanced in 2018 with a US$190 million loan from Blackstone Mortgage Trust, public records show.
According to New York City-based President and Co-Founder of Lodging Analytics Research & Consulting Ryan Meliker, the pricing is about $380,000 per room, prior to what he expects is a considerable amount planned capital improvements.
“I believe that reflects the balance of risks and rewards for the market today,” Meliker said. “The risk being a new union labor contract that we expect to drive labor costs up materially, a federal government that is negatively impacting inbound foreign arrivals and a new City administration with many unfriendly business campaign policies (though we don’t know if any will materialize).”
Meanwhile, Meliker added, the market has been one the nation’s outperformers over the past few years and the positive impact from the World Cup is expected to be sizeable in 2026. “The market is benefiting from high absolute occupancies and hopes of increasing office utilization and what is effectively a moratorium of new hotel supply across the market,” he continued. “Combined there are real risks across the market but also strong positives, which I believe this pricing (prior to capital expenditures) reflects.”
Argent Ventures, a vertically integrated real estate investment and development firm, recently acquired and converted the Crowne Plaza Times Square into the Hyatt Regency Times Square, which is also operated by Highgate.
Highgate has been active in the city as well having recently invested in the 1,331-room Row NYC.
In explaining why they liked this deal and asset, Alessandro Colantonio executive vice president and chief investment officer for Gencom told Hotel Investment Today, “The InterContinental New York Times Square represents a strong value-creation opportunity in today’s hospitality market. New York continues to demonstrate exceptional long-term fundamentals, and this asset, given its scale and prime location, is uniquely positioned for elevated performance. Built in 2010, it is one of the city’s newer large-format luxury hotels, offering meaningful and sustainable upside through thoughtful reinvestment.”
In reference to the partnership, Colantonio added, “Gencom is pleased to partner with Argent Ventures and Highgate on this acquisition. We’ve known and admired Highgate for nearly 40 years, and Argent brings deep expertise in the New York market. Together, this partnership creates a dynamic where one plus one truly equals three. With IHG’s strong luxury platform, we see a clear path to strengthening the hotel’s competitive position and unlocking long-term value.”
“Highgate is thrilled to complete another significant investment in New York, and to partner with Gencom and Argent Ventures,” said Zach Berger, principal. “Highgate has invested in New York across multiple cycles and multiple asset classes. It remains committed to fielding a best-in-class operating team in the market and delivering exceptional experiences for our guests and leading results for our partners. We are also excited to continue expanding our activities with IHG, and to lead this new chapter for the InterContinental New York Times Square.”
Hotel holiday displays that light up the season
The end-of-year holiday slowdown is settling in.
It was a difficult week for U.S. hotels as revenue per available room dropped 3.7% in the week of Nov. 30 to Dec. 6. Occupancy again led the decline, falling 1.9 percentage points. Absolute room demand dropped by more than 580,000 rooms, and average daily rate decreased 0.5%. Weekday (Sunday to Thursday) RevPAR retreated by 4.3%, led by occupancy declining 2.2 percentage points. Weekend (Friday and Saturday) RevPAR was also down but at half the rate of weekdays.
Hurricane markets pull down RevPAR comps further
As has been noted in previous analyses, the 13 hurricane markets affected by Hurricane Helene and Hurricane Milton in 2024 continued to have the largest bearing on U.S. performance, accounting for more than a point of the RevPAR decrease this week. Las Vegas was also a big contributor. Excluding both the 13 hurricane markets and Las Vegas, U.S. RevPAR was down 1.7%, occupancy fell 1.1 percentage points and ADR was flat (+0.2%). Weekday RevPAR among the remaining markets was also still down, but the 2.4% drop was less severe than the total U.S. results. Weekend RevPAR was nearly flat.
As a reminder, the hurricane market decline is due to decreasing room demand. A year ago, weekly demand in these markets was up 17.1%, whereas it is down 16% this week. Twelve of the 13 markets saw demand fall by more than 10% with only Macon/Warner Robbins, Georgia, up (+0.2%). Overall, hurricane markets accounted for 41% of the total U.S. room demand decline this week and 84% of the gross loss over the past six weeks.
Top 25 had its share of winners
While many markets saw RevPAR retreat, 11 of the top 25 markets reported RevPAR gains in the week led by New Orleans (+7%) and followed by St. Louis (+5%). Other winners included Anaheim (Orange County), Detroit, Nashville, Orlando, Phoenix, San Diego and San Francisco. The growth in most of these markets came from increased group demand. Collectively, group demand in luxury and upper upscale hotels was up 5.5% in these markets, with RevPAR increasing by 6.8% on equal gains in occupancy and ADR.
On the other end of the spectrum and among the top 25 markets, Tampa, a hurricane market, saw the largest RevPAR decrease (-28.7). That was followed by Seattle (-24.6%), and lesser but still double-digit declines in Las Vegas, Los Angeles and Philadelphia. Falling group demand, except in Tampa, was a key driver in these markets. The measure was down 35% collectively among luxury and upper upscale hotels, resulting in a 13.5% RevPAR decrease. The steep decrease in group demand was likely due to conference shifts.
Among markets outside the top 25, Wisconsin North saw the largest weekly RevPAR increase, up 36%, followed by Texas North, Louisiana North and four other markets where RevPAR grew by more than 11%. Weekend RevPAR was led by Wisconsin North (+96.8%) and followed by Buffalo, Milwaukee and the New Jersey Shore, where the measure was up by more than 20%. Both Buffalo and Milwaukee benefited from NFL football games.
Speaking of football, weekend RevPAR in the 95 college football markets tracked fell 1.7% over the 14 weeks of the regular season on declining occupancy and flat ADR. Among the larger football markets with 50,000-plus seat stadiums (51 markets), weekend RevPAR was down 1.4% this season.
Group demand down again
While some markets benefitted from group demand, the overall measure among luxury and upper upscale class hotels was down 7.9% from a year ago. In the 19 markets with convention/exhibit space of 500,000-plus gross square feet, group demand was down 5.9% this past week. Orlando was the big winner as group demand there shot up 17.3%. Over the past six weeks, group demand in the big convention markets is down 0.8% but up 1.2% in the next set of convention markets — 44 markets with exhibit space of 100,000 to 499,000 gross square feet.
Among branded hotels, luxury hotels in that size bracket saw RevPAR advance 1.6% during the week on ADR (+4.9%) as occupancy was down 2.1 percentage points. Upper upscale hotels saw a similar occupancy decrease but their ADR growth (+0.4%) was insufficient to offset the occupancy drop, resulting in a 2.7% RevPAR decline. RevPAR in the remaining chain scales ranged from down 3.8% in upper midscale to down 8.6% in economy.
November shows the largest RevPAR decline post-pandemic
From preliminary data, U.S. November hotel RevPAR is estimated to have dropped by 2.4%, the largest post-pandemic RevPAR decline and the sixth consecutive monthly decrease. Of the past eight months, RevPAR has only been positive one time and that’s because the measure was flat (0.0%). November’s retreat was led by occupancy, which also saw its largest post-pandemic decline. ADR was of little assistance as it was up by only 0.5%. As with the weekly results, the totals do not tell the entire story.
First, the month was negatively affected by an additional Sunday, which has the weakest RevPAR of the seven days, and the loss of a Friday, the second-highest RevPAR day. To underscore this shift on a day-matched basis — Sat., Nov. 1, 2025, to Sun., Nov. 30, 2025, versus Sat., Nov. 2, 2024, to Sun., Dec. 1, 2024 — November RevPAR was down by only 0.3%.
Second, the 13 hurricane markets were a significant drag on the month and will continue to be. If you exclude those markets, November RevPAR fell 1.3%, which is like the decreases seen June through September.
Third, if you remove the 13 hurricane markets and Las Vegas, the rest of the country saw November RevPAR drop 0.9%, which is also in line with previous months.
Global RevPAR growth moderates
After two weeks of high single-digit gains, global RevPAR on a same-store basis and excluding the U.S. moderated to 5% growth, all on ADR, since occupancy was flat. RevPAR growth was again led by the Gulf Cooperative Council, where RevPAR advanced by 14.5%, followed by Australia, India, Japan and Italy, which all saw double-digit growth. Of the large countries, only Canada, China and Mexico saw RevPAR decrease this week.
GCC has seen double-digit same-store RevPAR gains in five of the past six weeks. This week, strong ADR-led RevPAR growth was seen in Bahrain (+47.1%) and Qatar (+38.7%). The latter saw performance surge on the Formula 1 grand prix, Doha Forum, FIFA Arab Cup and more. The United Arab Emirates saw RevPAR advance 17.1% followed by Oman and Kuwait, where the measure increased by more than 10% in each country. The only country to see a decline this week was Saudi Arabia (-5.2%).
Canadian same-store RevPAR fell 12.8% on an 11.4% ADR decrease. Most markets saw growth, but the three largest ones (Montreal, Toronto and Vancouver) saw the measure fall with Vancouver’s RevPAR dropping by more than 58.8% on a 55.8% ADR decrease. The reason is simple: Taylor Swift. Last year, she performed the final three shows of the Eras Tour there, beginning on Fri., Dec. 6. Falling occupancy led to the declines in Montreal and Toronto.
Same-store RevPAR in Mexico was down 2.6% on equal declines in occupancy and ADR. Large decreases were seen in several key tourist destinations including Yucatan/Campeche, Mexico Caribbean, Baja California and Gulf of Mexico. The latter two markets saw RevPAR decline by 10.8% and 21.1%, respectively. Mexico City, Mexico Northwest and Pacific South all reported RevPAR gains of more than 8% this week.
Unlike in the U.S., global demand and RevPAR are on a trajectory for continued growth through the end of the year and into 2026.
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That’s promising. However, the flip side is that most B2B leaders have yet to embrace gen AI or even engage with it. A few leaders tell us they are unsure where the benefits would come from and whether the business impact justifies the investment. Some feel overwhelmed by the abundance of ideas and seek advice on what to prioritize.
In this article, we explore seven compelling use cases across the deal cycle by analyzing gen AI deployments and their impact on sales ROI and customer experience . These use cases can improve effectiveness and efficiency and start delivering near-immediate impact. We also examine actual deployments by leading organizations. Finally, we suggest key considerations that can help organizations establish a gen AI implementation strategy that aligns with their goals and desires to drive profitable growth in sales.
1. Next-best opportunity
B2B sellers often struggle with oversimplified rules, manual customer research, a lack of data integration, or inadequate training on sales tools. AI can help lead them to their “next-best opportunity.” It can process multiple disparate data sources to prioritize possibilities. Gen AI can parse significant amounts of unstructured data (for example, PDFs, flat files, or photographs) to provide advanced recommendations and instructions. Gen AI can also synthesize relevant information about leads onto a consolidated battlecard, allowing sellers to chase their next-best opportunity based on clear, critical information.This use case can significantly accelerate the time-consuming process of conducting account research, mapping relationships, and identifying additional stakeholders. Gen AI modules can be trained to answer questions by mining a variety of sources, such as news articles, company reports, and transaction data. The resulting outputs can be integrated directly into a company’s customer relationship management (CRM) to help sellers prioritize customers and opportunities.
Businesses that deal with a large number of products and leads are most excited about this use case. In the B2B Pulse Survey, B2B commercial leaders in construction materials, shipping, chemicals, or petrochemicals companies—where leads are often generated and managed manually—were disproportionately more enthusiastic about this use case compared with others.
2. Next-best action
Even when opportunities are prioritized based on engagement and intent data, some sales organizations struggle to know what steps are needed to take advantage of opportunities that require immediate engagement.
Gen AI and machine learning can improve guidance to sellers on the “next-best action” to take, such as whether to place a lead in a low-engagement nurturing segment for a later month or in the queue for a top-priority marketing campaign. Gen AI can also categorize leads by channel actions, such as identifying who to invite to a webinar or who may benefit from immediate one-to-one interaction. Gen AI can even personalize outreach, such as suggesting email or voicemail scripts based on churn risk.
In the B2B Pulse Survey, next-best action stands out as one of the most exciting use cases in industries such as tech services, durable equipment, and insurance, where sellers are faced with a relatively large set of options to expand accounts and advance opportunities.
3. Meeting support
Since sellers struggle with lots of complex information, preparing for key client meetings can be a time-intensive process. Gen AI and other types of automation can save sellers time and improve conversations. The technologies can synthesize critical information from multiple sources (such as service tickets or transaction data) and provide relevant insights in an easy-to-consume format. A large language model (LLM) can even draft talking points and responses to objections for more efficient preparation without sacrificing conversation quality.
Meeting support does not have to take a long time to deploy. There are readily available gen-AI-enabled tools that are relatively industry-agnostic, can reference meaningful sources across a wide array of industries, and can be customized easily with off-the-shelf solutions.
The meeting support use case tends to generate the most excitement among industries with long sales cycles, numerous meetings, and large deal values, where the savings on administrative time can be significant. For example, more than 40 percent of B2B Pulse Survey respondents in aerospace and defense, oil and gas refining, and energy distribution indicated they are excited about this use case.
4. Request for proposal responses
Responding to requests for proposals (RFPs) can be a time sink. But gen AI can improve the efficiency and accuracy of RFP responses, reduce response times, and manage internal tracking. Gen AI helps drive consistency and improve the customer experience as multiple functional teams give input on how to respond to an RFP.
This use case is exciting for leaders across a wide variety of industries, with particular interest from life sciences companies, which frequently handle highly complex, regulated, and data-intensive RFP responses that normally require extensive manual efforts to address. Roughly 40 percent of biopharmaceutical leaders and 30 percent of healthcare leaders responding to the B2B Pulse Survey were extremely excited about the potential for a gen-AI-enabled RFP responder
5. Smart pricing
The impact of AI on pricing can be huge. Many B2B industries rely predominantly on basic analytics and commercial acumen of the sales team. AI creates the opportunity for significant innovation. It allows B2B players to tailor models that have mostly been used only in high-paced B2C industries (for instance, online retail). The result is new opportunities for first movers and new risks for laggards.
There are several predominant applications of AI and gen AI for smart pricing. One is in AI-led price setting, in which the microsegmentation of customers allows for an assessment of customers’ willingness to pay and to buy at a given price point. Additional applications include gen-AI-enabled negotiation support and pricing administration. Companies have started to use gen AI to analyze publicly available data and interactions with customers and track the effectiveness and performance of negotiations, as well as create tailored arguments. This also equips sellers with a score and rationale for how much negotiation power they have. Gen AI is also proving effective in the use of automation in price administration, including system updates and approval workflows.
In the B2B Pulse Survey, smart pricing was prioritized by respondents in industries where pricing has a significant impact on profitability, and products have less differentiation and variability (for example, paper and packaging, energy distribution, and shipping)
6. Smart research assistant
High-performing B2B sellers spend considerable time researching customers, prospects, and products. Pulling together insights from corporate websites, annual reports, and earnings calls, as well as emails and internal data, takes significant time. This can be especially cumbersome for sellers who are trying to engage a customer on a live call while struggling to quickly locate, digest, and synthesize relevant information. This customer interaction has been transformed by gen AI, which can assist sellers with quick fact-finding during calls. As a result, sellers are sharper and more insightful, which improves the overall experience.
Respondents to the B2B Pulse Survey showed the highest average interest in the smart research assistant use case, with 27 percent saying they were excited about its prospects.
7. Smart coach
Given the length and complexity of some B2B sales processes and deal cycles, it’s often challenging for sales managers and leaders to effectively benchmark seller performance. Gen AI can analyze seller performance across all customer interactions to provide managers with a comprehensive view of performance and recommend targeted coaching based on seller-specific needs. It can also provide personalized performance insights directly to sellers to allow for personal development and growth.
B2B Pulse Survey respondents in service industries that use relatively consistent sales pitches are the most eager to help their sellers with gen-AI-enabled smart coaches. For example, 35 percent of leaders in the B2B insurance space indicated they are enthusiastic about the smart coach use case.
These seven case studies reveal the potential of gen AI to transform the end-to-end sales journey. Industry leaders are excited about these use cases, but they are even more interested in the next wave of innovation, agentic AI. With limited human intervention, agents can reason, interpret, and make autonomous decisions for an activity or workflow. Consider next-best-action use cases: Agentic AI will not only identify specific actions (such as classifying a lead as medium priority, requiring one to two warm-up outreach emails) but will actually execute the action by automatically reaching out to a prospect, evaluating their interest, and responding back (for example, by sending a message that reads, “We noticed you were interested in a specific product, so we wanted to provide more detail”). AI agents can also nurture a relationship with a sales prospect through multiple communications about potential actions, such as setting up a meeting between the customer and seller. AI agents are so powerful that they have the potential to bring all the seven use cases to the next level.
Five key lessons for deploying gen AI in B2B sales
The seven case studies illustrate how companies can leverage AI to fundamentally rewire their sales capability for outsize, profitable growth. Effective deployment of gen AI is crucial for success. Whether starting their first pilot or scaling initial efforts, any company looking to achieve lasting change across their sales organization should consider these five lessons.
Start with the problem, not the technology
The decision to use gen AI or any other technology should be guided by specific business considerations. For B2B sales, the primary consideration should be identifying where this technology can propel outsize, profitable growth. Companies can start by pinpointing core business challenges, such as lead acquisition, servicing important accounts, or managing services more effectively. Then they can determine the use cases that will deliver the most value. Once priorities are clear, B2B leaders can decide whether these needs are best met by technologies such as rule-based automation, machine learning, AI, or gen AI.
In some cases, sales organizations may not need to pivot to gen AI, especially if foundational processes such as order management or lead routing are still manual. When error tolerance is very low, simple automation with direct links to the source might be a sufficient and more reliable approach, avoiding the potential risks of gen AI hallucinations. The key to designing and developing the best solutions is a clear understanding of the business problem. Only then can a sales leader evaluate whether gen AI is the right choice for their needs.
Keep the seller at the center
To get the most value from a gen AI solution, it’s imperative to ensure that its design is focused on users’ needs. B2B organizations can start by evaluating current sales processes to find ways to free up sellers’ time or provide valuable insights to sellers when they need them most. It also means digging into the customer’s journey. Sellers who can use the right insights and efficiencies to create more moments of customer delight will be more excited to use the solution.
Commercial leaders can ask themselves the following questions to ensure that gen AI solutions are seller-centric:
*- Clear: Is the output easy to understand?
*- Understandable: Can sellers easily explain outputs to customers?
*- Prescriptive: Are outputs clearly linked to specific actions for sellers?
*- Reliable: Will sellers trust outputs and find information consistent and accurate?
If the answer to any of these five questions is no, it’s worth revisiting the solution’s design—including critical features, data sources, analytics outputs, or how information is presented. On the other hand, positive answers to these questions will make it more likely for the gen AI use case to be enthusiastically adopted by sellers.
Buy the easy stuff and build for competitive advantage
It’s no surprise that most organizations don’t build entire gen AI capabilities on their own from scratch. Even when they opt to build for a specific use case, a significant portion of the functionality (such as an LLM) often comes from publicly available, off-the-shelf solutions that can be fine-tuned. In this sense, a “build” approach is more accurately described as “buy plus build.”
To decide between a “buy” or a “buy-plus-build” strategy, it’s important to set clear commercial priorities for high-impact gen AI use cases that can give your sales organization an edge. For lower-complexity use cases with largely standard functionality (such as summarizing meeting transcripts), leading organizations often opt to buy and deploy a ready-made gen AI solution quickly. For high-value use cases with the potential for unique performance and competitive advantage (such as delivering the right offer at the right time), it’s better to take a buy-plus-build path where investments in targeted development beyond out-of-the-box functionality can enable greater impact. Making the right choices on when to buy versus when to invest in building custom solutions for strategic advantage can set leaders apart from the competition.
Balance immediate impact and lasting capabilities with a clear AI strategy
As commercial leaders start to deploy gen AI use cases in B2B sales, it’s essential to establish and maintain a clear vision of the overall commercial tech stack and the enterprise AI strategy and architecture. Inconsistent architectures can lead to wasted efforts, incompatible solutions, and increased costs. By ensuring alignment from the start, organizations can prevent fragmentation from disparate development efforts, and integrate various AI initiatives seamlessly, maximizing their value.Leading organizations can blueprint efforts in a matter of weeks, allowing them to swiftly develop effective gen AI use cases while maintaining a cohesive framework. They do so by carefully scoping minimal viable products (MVPs) and leveraging partners when they don’t have the right people internally. Early successes act as lighthouses to encourage excitement, mobilize the organization, and secure support and resources for scaled implementation.
While quick wins are important, they should not come at the expense of foundational capabilities. Investing in the right technological infrastructure is vital for long-term success. This includes robust data management and governance, comprehensive data processing capabilities, and a modernized tech stack. Equally important is talent. Ambitious organizations cultivate teams with the skills to build, maintain, and enhance gen AI functionalities over time. This involves hiring the right talent and continuously upskilling employees to foster a culture of innovation and adaptability. By striking the right balance between near-term impact and long-term capabilities, organizations can ensure their gen AI journey is both effective and sustainable.
Invest in seller adoption from the get-go
Commercial leaders are often eager to implement new gen AI solutions to boost performance. However, getting sales teams to adopt these solutions sustainably and at scale can be more challenging than launching the technology. A seller-centric design and an experimentation mindset that leads to first MVPs are a good start, but leaders need to invest time and effort to maximize adoption and produce real impact. When deploying AI solutions in sales, it’s crucial to take an agile approach to development, including an iterative process with frequent test-and-learn cycles rooted in seller feedback and continuous refinement within tightly linked business and tech teams.
Effective deployment also requires careful change management, a practice that’s far too often overlooked. Leading organizations use a variety of strategies to prepare and support sellers for new AI solutions. These include frequent communications and setting clear expectations, using seller champions and sounding boards, providing training sessions and recognizing success stories, and employing thoughtful use of new solutions by sales leaders. Incentivizing sellers who experiment with AI and celebrating catching errors as part of innovation can foster a culture of continuous improvement.
Finally, AI centers of excellence can help accelerate adoption and scale gen AI to more use cases. These centers can prioritize resources, centralize funding, ensure proper change management, and drive responsible use.
While many B2B sales organizations are still in the early stages of technological development, leading companies are already scaling their gen AI capabilities. Commercial leaders whose companies are experiencing higher growth tend to be more enthusiastic about gen AI and are implementing multiple use cases to transform their growth strategies and seller journeys. Gen AI can empower teams by providing better insights, driving higher conversion rates, and boosting productivity. Autonomous agents may deliver even more impact. With the right growth strategy and go-to-market model in mind, and the willingness to turn interest in gen AI into action, B2B leaders can unlock a future with enormous potential.
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