The development comes at a time when startup mentorship and accelerator access continue to remain highly competitive. While mentored startups survive at twice the rate of non-mentored companies, nearly 97% of founders who apply to accelerator programs fail to secure entry. As a result, many early-stage entrepreneurs struggle to access experienced guidance during critical growth phases.

Through the acquisition, Startup Science aims to address this challenge by creating a scalable mentorship infrastructure for startup founders, entrepreneurs, venture-backed companies, and innovation-driven businesses. The company stated that the advisory ecosystem for startups remains massive yet largely unstructured. Currently, an estimated 200,000 to 500,000 mentors and advisors actively support startups across the United States through informal networks and introductions, which many founders cannot easily access.

Moreover, while platforms such as Fiverr connect businesses with freelancers and contractors, Startup Science believes the startup ecosystem lacks a dedicated infrastructure specifically built for founder mentorship and advisory services. Consequently, the Startup Science Advisors system seeks to bridge that gap by introducing structure, accountability, and intelligent matching into the mentorship process.

Colin Christensen developed Sphere after mentoring more than 2,500 entrepreneurs across five continents. Throughout his work, he trained mentors through translators in communities where entrepreneurship serves as a key pathway out of poverty. In addition, he collaborated with tier 1 VC firms in Riyadh, helping venture-backed founders scale deep tech businesses.

Importantly, Christensen identified a recurring issue within the startup ecosystem: founders need immediate guidance for the problems directly impacting their businesses instead of generalized courses that fail to address urgent operational challenges.

“The mentor-entrepreneur relationship is the most sacred, the most important one in this ecosystem,” said Christensen, now Head of Advisory at Startup Science. “Whether a founder is selling salsa in Honduras or scaling AI in the Middle East, the fundamentals are the same. The difference is whether they have a system to work through those fundamentals with a mentor or whether they are doing it alone.”

The newly launched Advisors module matches startup founders with mentors based on their startup lifecycle phase, business expertise, and operational goals. Furthermore, mentors can monitor founder progress between sessions, track deliverables and outcomes, and manage larger advisory practices without losing continuity or context.

At the same time, founders remain engaged between mentorship sessions through structured check-ins, reducing the communication gaps that often emerge in traditional advisory relationships. Startup Science designed the platform to scale startup mentorship similarly to how Upwork transformed freelance work by introducing infrastructure, matching systems, workflow management, and accountability into a previously fragmented market.

“Colin has experience in startup advisory that is distinct and deeper than anyone on our team, including me,” said Gregory Shepard, founder and CEO of Startup Science. “That is exactly the kind of expertise you acquire, not replicate.”

The Advisors module is currently live on the company’s official platform at Startup Science Advisors.

However, the companies did not disclose the financial terms of the acquisition.

As startup ecosystems continue to expand globally, structured mentorship and founder support systems are becoming increasingly critical for entrepreneurial success. With the acquisition of Sphere and the launch of the Advisors module, Startup Science is positioning itself to strengthen startup mentorship infrastructure and improve access to expert guidance for founders worldwide.

Despite the strong earnings performance, the company’s shares remained largely flat in volatile extended trading after investors reacted to a sharp increase in operating expenses.

Demand for AI cloud infrastructure services from so-called “neocloud” providers such as CoreWeave and its peer Nebius has accelerated significantly as businesses race to secure computing power for generative AI models, machine learning systems, and enterprise AI applications.

CoreWeave reported total first-quarter revenue of $2.08 billion, exceeding analysts’ average estimate of $1.97 billion, according to data compiled by LSEG. However, the company’s operating expenses more than doubled year-on-year to $2.22 billion during the quarter.

The AI infrastructure business remains highly capital-intensive, and CoreWeave continues investing aggressively in expanding its data centre capacity to meet growing customer demand. The company’s expansion strategy requires billions of dollars in upfront infrastructure investments, particularly in advanced GPUs, AI servers, and cloud computing facilities.

A major competitive advantage for CoreWeave comes from its specialised AI infrastructure and close partnership with Nvidia, which provides the company with early and large-scale access to some of the world’s most sought-after AI chips and hardware technologies. Consequently, CoreWeave has become a preferred cloud provider for AI startups as well as enterprise customers seeking alternatives to capacity-constrained traditional cloud providers.

The company has recently secured several high-profile deals that further strengthen its position in the rapidly expanding AI cloud computing market. Over the past month, CoreWeave signed an expanded $21 billion agreement with Meta for additional cloud computing capacity. Additionally, the company entered into a $6 billion deal with trading firm Jane Street and secured another partnership agreement with Anthropic.

CoreWeave also reported a substantial increase in its revenue backlog, which reached $99.4 billion as of March 31, compared with $66.8 billion at the end of December. The expanding backlog highlights the growing global demand for AI infrastructure, cloud GPU services, and large-scale computing capacity required for next-generation artificial intelligence development.

CoreWeave’s latest financial results underscore the explosive growth in the AI infrastructure market as enterprises and AI developers continue investing heavily in cloud computing and high-performance AI systems. While rising operating costs reflect the capital-intensive nature of the business, CoreWeave’s expanding customer base, strategic partnerships, and massive revenue backlog position the company as a major player in the global AI cloud ecosystem.

The company linked the layoffs to what it described as an “agentic AI-first operating model” rather than employee performance or short-term cost-cutting measures. According to sources, co-founders and chief executives Matthew Prince and Michelle Zatlyn shared the announcement with employees through an internal message.

Cloudflare employed 5,156 full-time workers at the end of 2025, based on company filings. Additionally, the company expects to incur restructuring charges ranging between $140 million and $150 million, with most expenses expected during the second quarter of 2026.

In a company blog post, Prince and Zatlyn revealed that Cloudflare increased its internal use of AI tools by more than sixfold during the past three months. “The way we work at Cloudflare has fundamentally changed,” the executives wrote, adding that employees across departments already use “thousands of AI agent sessions each day.”

The leadership team stated that Cloudflare is now “reimagining every team and function” for what it called the “agentic AI era,” where AI systems increasingly handle software development, operations, finance, customer support, and internal workflows. Furthermore, the company clarified that the restructuring reflects a redesign of processes and operational roles rather than concerns related to productivity or immediate financial challenges.

Cloudflare also said the restructuring aims to help the organisation adapt to faster AI-assisted execution, automation, and accelerated product development cycles. According to The Wall Street Journal, the company rapidly expanded AI adoption internally in recent months, prompting major operational shifts across multiple departments.

The layoffs come despite strong financial performance from the company. For the first quarter, Cloudflare reported a 34% year-on-year increase in revenue, reaching $639.8 million. Meanwhile, adjusted earnings stood at 25 cents per share, exceeding Wall Street expectations. However, the company’s shares declined in extended trading after it issued second-quarter revenue guidance slightly below market forecasts. Cloudflare projected second-quarter revenue between $664 million and $665 million.

Prince described artificial intelligence as “a fundamental re-platforming of the Internet” and emphasized that the AI transition represents one of the biggest growth opportunities in the company’s history.

Cloudflare now joins a growing list of technology companies reshaping their workforce structures around artificial intelligence, automation, machine learning, and AI-powered software development. As enterprises increasingly integrate generative AI and intelligent automation into daily operations, many tech firms continue redesigning teams and workflows to align with the rapidly evolving AI economy.

Cloudflare’s workforce reduction signals the accelerating shift toward AI-driven business models across the global technology industry. While the company continues delivering strong financial growth, its restructuring highlights how artificial intelligence is transforming operational strategies, workforce planning, and the future of enterprise software development.

The venture investment arm of Meituan led the funding round, pushing Moonshot AI’s valuation to more than $20 billion, according to a statement released by financial advisor HF Capital, which advised several investors involved in the transaction. Additionally, the company reported that its annual recurring revenue crossed $200 million in April, driven primarily by subscriptions to its Kimi chatbot and AI model services.

A spokesperson for Moonshot AI did not respond to requests for comment. However, a representative from Meituan’s Long-Z Investments confirmed the firm’s participation in the round.

The latest investment demonstrates the rapid growth of Moonshot AI, which has increased its valuation more than fourfold within just a few months. Toward the end of last year, the Beijing-based startup raised $500 million at a valuation of $4.3 billion. Earlier this year, the company secured another $700 million at a $10 billion valuation. Subsequently, it was reported that the startup sought an additional $1 billion in funding through an expanded fundraising round.

Investors have increasingly directed capital toward a select group of Chinese AI startups that aim to compete globally in generative AI, large language models, AI chatbots, and enterprise AI services. Meanwhile, DeepSeek has reportedly begun raising external capital for the first time, attracting strong interest from state-backed investors at a potential valuation of up to $50 billion.

At the same time, Moonshot AI’s competitors, including MiniMax and Zhipu AI, have achieved valuations exceeding $30 billion following their strong market debuts in Hong Kong earlier this year. The developments reflect the accelerating momentum in China’s artificial intelligence ecosystem as companies race to develop globally competitive AI technologies.

Moonshot AI founder Yang Zhilin established the company after working at Meta Platforms and Google. The startup currently offers tiered subscription plans for its Kimi chatbot while also providing AI infrastructure and underlying model technology to enterprise customers.

As investor confidence in generative AI, enterprise AI solutions, and large language models continues to rise, Moonshot AI is rapidly emerging as a significant challenger to major Western AI companies in the global technology landscape.

“Freshworks began Q1 with strong momentum, building on our 2025 successes and achieving our sixth straight quarter of exceeding expectations,” said Dennis Woodside, CEO and President of Freshworks adding that demand for its EX platform and AI Copilot offerings continued to drive expansion. This reflects the increasing adoption of AI-powered customer and employee experience solutions across enterprises.

However, the company reported a GAAP operating loss of $8.1 million in Q1 2026, although it narrowed from a loss of $10.4 million a year earlier. At the same time, the company reversed its position from Q4 2025, when it had recorded a GAAP operating profit of $39.7 million, highlighting ongoing margin pressures in the cloud software market.

Meanwhile, Freshworks announced plans to reduce its global workforce by approximately 11%, impacting around 500 employees, as part of a broader restructuring strategy. This move comes as global SaaS companies face increasing pressure on growth efficiency and profitability. The layoffs will affect operations across India and the United States, signaling a shift toward leaner operational models.

The company expects to incur one-time restructuring charges of about $8 million, with most of these costs likely to be recognised in the second quarter of 2026, said Tyler Sloat during the company’s Q1 earnings call on May 6. This restructuring aligns with broader tech industry cost optimisation trends.

In terms of adjusted performance, non-GAAP operating income stood at $41 million, down from $46.4 million in the previous year, while margins contracted to 17.9% from 23.6%. Sequentially, the figure remained largely flat compared with $41.6 million in Q4, although margins declined, indicating cautious profitability trends despite steady revenues.

Additionally, GAAP net loss per share came in at $0.02, compared with breakeven ($0.00) a year ago. In contrast, the company had reported a profit of $0.67 per share in Q4 2025, reflecting a sharp sequential drop. On a non-GAAP basis, earnings per share declined to $0.11 from $0.18 a year earlier and also fell from $0.14 in the previous quarter. Despite this, the company maintained profitability on an adjusted basis, even as per-share earnings softened.

Furthermore, GAAP refers to standardised accounting principles that companies must follow, whereas non-GAAP metrics exclude items such as stock-based compensation or one-time expenses to provide a clearer view of underlying operating performance—an important distinction for investors tracking earnings analysis and financial performance metrics.

On the cash flow front, Freshworks maintained steady performance, with operating cash flow rising to $62.4 million from $58 million a year ago. Adjusted free cash flow stood at $55.8 million, while the company ended the quarter with a strong cash position of $780.4 million in cash and equivalents. This reinforces its financial stability amid evolving market conditions.

Following the earnings announcement, Freshworks’ shares rose about 2% to trade at around $0.19 apiece. However, the stock remains down roughly 26% year-to-date, reflecting broader volatility in technology stocks and investor sentiment around growth-oriented companies.

Importantly, the company secured two of the largest deals in its history during the quarter, including its first contract exceeding $1 million in annual recurring revenue (ARR). This milestone highlights increasing traction in the enterprise segment and strengthens its position in the enterprise SaaS market.

Among key operating metrics, the number of customers contributing over $100,000 in ARR increased 29% year-on-year. Meanwhile, net dollar retention stood at 106%, slightly lower than 108% in Q4 2025, indicating stable but moderating customer expansion trends.

Looking ahead, Freshworks expects Q2 2026 revenue to range between $232 million and $235 million. Additionally, the company raised its full-year revenue guidance to between $958 million and $964 million, signaling continued confidence in achieving double-digit growth in the global SaaS landscape.

“As we grow Freshworks to a $1 billion ARR company and beyond, our EX business represents the primary and largest growth opportunity,” Woodside said during the company’s earnings call. This outlook underscores the company’s strategic focus on scaling its EX platform and expanding its enterprise footprint.

The company also highlighted strong adoption of its AI offerings. “In Q1, Freddy AI Copilot customer growth exceeded 80% year-on-year, while the attach rate in new deals above $30,000 ARR was over 65%. Within its EX business, customer penetration for AI crossed 20%, nearly doubling from a year ago, and about one-third of all new EX customers adopted Copilot,” Woodside said.

Freshworks’ Q1 2026 results reflect a balanced narrative of steady revenue growth, rising enterprise adoption, and expanding AI capabilities, alongside profitability pressures and workforce restructuring. As the company continues to invest in AI innovation, employee experience platforms, and enterprise software solutions, it remains well-positioned to capitalise on long-term growth opportunities while navigating near-term market challenges.

In a highly competitive AI market, Sierra has actively highlighted its rapid growth trajectory. Initially, the company started with just four design partners a few years ago. However, it now claims that more than 40 percent of the Fortune 50 companies use its platform. Additionally, AI agents running on Sierra’s platform currently handle billions of interactions, including mortgage refinancing, insurance claims processing, product returns, and nonprofit fundraising campaigns.

Furthermore, the AI startup has demonstrated aggressive revenue expansion. The company reported reaching $100 million in annual recurring revenue (ARR) in late November, and shortly afterward, it announced that it had scaled to $150 million in ARR by early February. This rapid growth reflects both increasing enterprise demand for AI solutions and the significant investments required to implement them.

Bret Taylor, who also serves as chairman of OpenAI and previously worked as co-CEO of Salesforce, has emphasized that agentic AI can ultimately reduce costs and increase revenue for businesses. However, he has also acknowledged that companies often face high upfront costs during the initial deployment phase.

This trend recently surfaced during a discussion at one of the events. During the conversation, Praveen Neppalli Naga, CTO of Uber, explained how the company rapidly consumed its AI budget after adopting agentic AI tools late last year. At the same time, he noted that Uber has started to observe meaningful results from these investments.

Notably, Uber has already integrated AI deeply into its engineering workflows. Approximately 10 percent of all code produced across its 8,000 engineers and technical staff is now generated autonomously. He added that “10% at our scale is huge.” In a practical demonstration, Uber assigned one team to build a new hotel-booking integration entirely using agentic workflows. Consequently, the team completed a project that would typically take a year in just six months.

Meanwhile, Sierra continues to expand its product capabilities beyond customer-facing AI agents. In April, the company launched Ghostwriter, an “agent as a service” tool that enables users to build other AI agents. With this feature, users can describe their requirements in natural language, and Ghostwriter autonomously creates and deploys specialized agents to perform those tasks.

For Bret Taylor, this innovation supports a broader vision he shared at the HumanX conference in San Francisco. He argued that many enterprise software tools remain underutilized, as employees interact with platforms like Workday only during specific events such as onboarding or open enrollment. Therefore, the AI startup and its investors envision a future where users no longer need to navigate complex enterprise systems, as AI agents will handle tasks seamlessly in the background.

Notably, GameStop has offered $125 per share in a 50-50 mix of cash and stock, which represents a premium of about 20% based on eBay’s Friday closing price. Meanwhile, eBay’s market capitalization stands nearly four times larger than GameStop’s, making this acquisition attempt highly ambitious and unconventional in the mergers and acquisitions landscape.

Furthermore, Cohen revealed in a letter to eBay’s board that GameStop has already secured a 5% stake in eBay through shares and derivatives. According to a report, which first covered the unsolicited bid, Cohen aims to significantly enhance GameStop’s valuation by leveraging synergies between the two companies.

In addition, Cohen emphasized that combining eBay and GameStop would unlock major opportunities to increase earnings and streamline operations. “It could be a legit competitor to Amazon,” Cohen said about eBay. He also projected that GameStop could reduce eBay’s annualized costs by $2 billion within 12 months of closing, thereby boosting earnings per share.

Moreover, Cohen highlighted that GameStop’s 1,600 U.S. stores could function as a nationwide infrastructure for authentication, intake, fulfillment, and live commerce, strengthening eBay’s operational capabilities. He further stated that he remains ready to initiate a proxy fight if eBay’s board does not engage with the proposal.

However, eBay has not yet responded to requests for comment regarding the offer. Despite this, Cohen reiterated his long-term vision, stating, “eBay should be worth—and will be worth—a lot more money.” He added, “I’m thinking about turning eBay into something worth hundreds of billions of dollars.”

Cohen, widely recognized as a key figure during the 2021 meme-stock frenzy, has built a reputation for making bold and unconventional investment decisions that influence market dynamics. Consequently, this proposed deal could disrupt traditional M&A strategies, as companies rarely attempt to acquire targets significantly larger than themselves without relying heavily on debt or equity financing.

To support the transaction, Cohen has already arranged financial backing, including a commitment letter for approximately $20 billion in debt from TD Bank. Additionally, he may seek further investment from external sources such as Middle Eastern sovereign wealth funds, according to the report.

If the deal materializes, Cohen confirmed that he will serve as CEO of the combined entity. He joined GameStop’s board in January 2021 and later assumed the CEO role, where he implemented aggressive cost-cutting measures that restored profitability.

Historically, GameStop gained global attention during the meme-stock rally when retail investors drove its stock price up by more than 1,700%. Nevertheless, the company continues to face structural challenges as the gaming industry shifts toward digital downloads and online platforms. Recently, GameStop reported a 14% decline in fourth-quarter revenue.

In contrast, eBay, founded in 1995 by Pierre Omidyar, has demonstrated resilience by forecasting second-quarter revenue above Wall Street expectations. The company has benefited from strong demand for collectibles, motor accessories, and live-streamed auctions.

As of Friday’s close, GameStop’s market valuation stood at nearly $12 billion, while eBay’s market value reached approximately $46 billion. Additionally, their shares have risen by 32.1% and 19.5%, respectively, this year, reflecting continued investor interest in both companies.

GameStop’s proposed acquisition of eBay marks a potentially transformative moment in the global e-commerce and retail industry. While the deal faces significant financial and strategic hurdles, it underscores Ryan Cohen’s aggressive growth strategy and ambition to position the combined entity as a formidable competitor to Amazon. If successful, the transaction could redefine industry dynamics, accelerate digital commerce innovation, and reshape the future of online marketplaces.

Through this acquisition, Meta strengthens its position at the forefront of robotic AI innovation. “We acquired Assured Robot Intelligence, a company at the frontier of robotic intelligence designed to enable robots to understand, predict, and adapt to human behaviors in complex and dynamic environments,” a Meta spokesperson said in a statement. The startup, co-founded by Lerrel Pinto and Xiaolong Wang, will see both founders join Meta as part of the deal. Previously, Wang worked as a researcher at Nvidia, while Pinto co-founded Fauna Robotics before exiting in 2025. Meanwhile, Amazon acquired Fauna Robotics in March to strengthen its own humanoid robotics programme. Assured Robot Intelligence operated primarily out of San Diego and New York.

Following the acquisition, the team will join Meta Superintelligence Labs and collaborate closely with Meta Robotics Studio, an internal division launched last year to build foundational technologies for humanoid robots. Moreover, the spokesperson stated that the team “will bring a deep expertise in how we can design our models and frontier capabilities for robot control and self-learning to whole-body humanoid control.”

Importantly, Meta continues to expand its robotics ambitions beyond a single acquisition. The company is actively developing in-house humanoid hardware alongside the underlying AI stack, including sensors, software, and core systems that it plans to make available across the broader robotics ecosystem. According to earlier reports, Meta aims to replicate the role of Google’s Android and Qualcomm’s chip ecosystem in smartphones by building a foundational platform for the humanoid robotics industry.

At the same time, the humanoid robotics space continues to gain rapid momentum, with major players such as Tesla, Google, and Amazon significantly increasing investments in robotic automation and AI-driven systems. Consequently, Meta’s latest move intensifies competition in what analysts view as a potentially trillion-dollar market over the coming decades.

Furthermore, the acquisition comes just two days after Meta raised its projected capital expenditure for 2026 by $10 billion, bringing the total range to between $125 billion and $145 billion. The company attributed the increase to rising component costs and additional investments in AI data centres. In recent years, Meta has also redirected substantial resources away from its augmented reality metaverse initiative toward artificial intelligence. Recently, the company launched a new large language model, Muse Spark, positioning it against offerings from Google, OpenAI, and Anthropic.

However, investors have responded cautiously to Meta’s aggressive spending strategy. The company’s shares declined following its earnings announcement and dropped 9.4% over the past five days, closing the week at $608.75. Analysts at Mizuho noted that while Zuckerberg’s long-term vision still lacks detailed clarity, its direction is becoming increasingly evident. “It remains vague, but we can see his agentic, consumer-focused vision start to take shape,” the analysts wrote. “The improving confidence from management was palpable.”

Meanwhile, in an internal meeting reported by The Wall Street Journal, Zuckerberg directly linked Meta’s rising AI investments to workforce reductions. He explained that “compute and infrastructure” alongside “people-oriented things” represent the company’s primary cost drivers, adding, “That means that we do need to take down the size of the company somewhat.”

As a result, Meta is expected to cut approximately 8,000 jobs, representing around 10% of its workforce, in the coming weeks to offset escalating AI-related expenditures. Zuckerberg further elaborated on the relationship between AI efficiency and workforce size, stating, “If a team used to take 50 or 100 people and now it takes 10, having 50 or 100 people on that team can actually be counterproductive going forward, so I think we need to fix that.”

Nevertheless, he clarified that workforce reductions do not necessarily translate into fewer opportunities, suggesting that AI could enable remaining employees to “spin up more new projects” across the organization.

As Meta continues to invest heavily in AI infrastructure and robotics platforms, the company is positioning itself to play a foundational role in shaping the future of intelligent automation and next-generation technology ecosystems.

With this move, Uber aims to increase user engagement and unlock new revenue streams by integrating end-to-end travel services into its ecosystem. As competition intensifies in the mobility and lifestyle space, the company is actively positioning itself to capture a larger share of consumer spending across transportation, accommodation, and dining.

The company announced the feature at its annual GO-GET event, where it confirmed that U.S. users can now search and book from over 700,000 hotels worldwide directly within the Uber app. Expedia’s extensive travel inventory powers the feature, while vacation rental listings from Vrbo, owned by Expedia, will join the platform later this year.

Additionally, the partnership reflects strong executive alignment, as Dara Khosrowshahi, CEO of Uber, previously led Expedia before joining Uber in 2017. This strategic connection further strengthens the collaboration between the two companies.

Moreover, Uber stated that members of its Uber One subscription program will receive at least 20% discounts on a selection of 10,000 hotels and earn 10% back in Uber Credits on bookings. Users can easily access the new “hotels” tab on the app’s home screen, apply filters based on price, ratings, and amenities, and complete bookings using their existing Uber wallet, thereby ensuring a seamless user experience.

Furthermore, Uber continues to expand its travel-focused offerings. Starting June, the company will extend Uber One benefits internationally, while it will introduce a new “travel mode” that provides location-specific ride guidance along with curated recommendations for dining and attractions.

In addition, Uber has rolled out several new features to enhance convenience and personalization. The “eats on the way” feature allows riders in select U.S. cities to pre-order snacks or drinks during premium rides. Meanwhile, the “shop for me” feature enables users to request items from stores that are not currently listed on Uber Eats.

The company has also introduced AI-powered voice booking and a unified search function that integrates rides, food, and retail services within a single interface. Through these innovations, Uber is actively advancing its ambition to become a “super app” that delivers multiple services through one platform.

Uber reported that its Uber One membership base reached 46 million users in the fourth quarter of 2025, marking a 55% year-on-year increase. This growth underscores the rising adoption of subscription-based models and highlights Uber’s expanding ecosystem.

Uber’s integration of hotel booking services in partnership with Expedia signals a major step in redefining digital travel and mobility platforms. As consumers increasingly demand convenience, personalization, and integrated services, Uber’s super app strategy positions it to lead the next phase of innovation in the global travel and lifestyle economy.

Notably, this marks the first time LinkedIn has disclosed sales figures for a core AI-driven product. The platform, which has surpassed 1 billion members globally, continues to generate a significant portion of its revenue by offering advanced tools to sales and recruiting professionals. Although Microsoft reports LinkedIn’s overall growth within its productivity and business processes segment, it does not provide standalone revenue figures for the platform.

Meanwhile, LinkedIn has introduced two major agentic AI-powered hiring solutions tailored for different business needs—one designed for large enterprises and another for small businesses. These systems enable an AI agent to interpret instructions from human recruiters, understand hiring requirements, and efficiently scan LinkedIn profiles to identify the most suitable candidates for further engagement. As a result, recruiters can streamline candidate sourcing and improve hiring efficiency.

Furthermore, LinkedIn stated that it extensively tested some of these AI-driven tools for nearly a year before officially launching them. The company emphasized that these solutions now help recruiters save time and achieve higher response rates when reaching out to potential candidates, thereby enhancing overall recruitment productivity.

“Recruiters told us half their day was low-value work, so we made a bet on understanding their pain to get our solution right,” Dan Shapero, LinkedIn’s new CEO who took over last week, said in a statement. “That focus on the customer, not racing to launch an AI agent, was the right one, and hitting this milestone shows it.”

LinkedIn’s strategic investment in agentic AI recruitment tools underscores a broader shift toward automation and intelligent hiring solutions in the HR technology landscape. As demand for faster and more effective talent acquisition continues to rise, AI-powered platforms like LinkedIn will play a critical role in shaping the future of work and recruitment.