Business software startup Rippling hopes the answer is yes.

The company is launching a product called Talent Signal, which uses AI to gauge employee performance based on task-specific metrics, Bloomberg reported Wednesday (Sept. 25).

The tool can spot patterns a manager might not notice, helping companies better use resources while determining which employees may need fast-tracking or additional guidance, the report said.

“In the ideal case, the manager would pull up a chair next to the employee and spend 90 days with them,” coaching them, said Rippling Chief Operating Officer Matt MacInnis, per the report.

While few managers have time for that sort of effort, AI does, the report added. Those who have tested Talent Signal said the tool lets them set aside preconceived notions and look objectively as they evaluate an employee’s performance.

MacInnis acknowledged some people might find the product unsettling, but it’s no less strange than a manager tracking a new employee, and it offers less bias, the report said.

The standard 90-day evaluation “can’t be about the vibe,” MacInnis said, per the report. “It’s got to be about the facts.”

Rippling’s workforce management platform combines human resources, informational technology and finance functions to create what it calls a “single source of truth” for employee data. The company raised $200 million in a Series F round in April that valued Rippling at $13.5 billion.

“Rippling’s core thesis is that employee data is critical to a surprisingly large number of business systems, including the ones well outside of HR,” CEO Parker Conrad said at the time.

Meanwhile, experts interviewed by PYMNTS have stressed the need for a balanced approach to AI that includes human intervention. Gillian Laging, co-founder of Scopey, a scope management platform, argued for built-in human oversight, pointing to her firm’s practice of having users review AI-drafted scopes of work before passing them on to clients.

“This approach acknowledges that while AI can dramatically speed up certain processes, human judgment remains invaluable,” PYMNTS reported this month. “For instance, an AI might draft a comprehensive project scope, but a seasoned professional can spot nuances, potential issues or client-specific considerations that the AI might miss.”

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Meanwhile, industry figures like Appian CEO Matt Calkins demand stronger IP protections, underscoring the challenges facing policymakers and businesses in the rapidly evolving AI landscape.

European Tech Leaders Call for AI Regulatory Certainty

A group of European business leaders, researchers and institutions penned an open letter urging the European Union to provide more transparent AI development regulations. The signatories, including Meta founder and CEO Mark Zuckerberg, Klarna CEO and co-founder Sebastian Siemiatkowski and Spotify founder and CEO Daniel Ek, warned that fragmented and inconsistent regulatory decisions could hinder Europe’s competitiveness in AI.

The letter emphasized the importance of “open” AI models and “multimodal” technologies. Without them, “the development of AI will happen elsewhere — depriving Europeans of the technological advances enjoyed in the U.S., China and India.”

The signatories said these technologies could “turbocharge productivity, drive scientific research and add hundreds of billions of euros to the European economy.”

However, the current regulatory environment in Europe was described as an obstacle. The letter stated that “regulatory decision making has become fragmented and unpredictable, while interventions by the European Data Protection Authorities have created huge uncertainty about what kinds of data can be used to train AI models.”

The tech leaders presented Europe with a choice in the letter.

“It can choose to reassert the principle of harmonization enshrined in regulatory frameworks like the GDPR and offer a modern interpretation of GDPR provisions that still respects its underlying values, so that AI innovation happens here at the same scale and speed as elsewhere,” the letter said. “Or, it can continue to reject progress, contradict the ambitions of the single market and watch as the rest of the world builds on technologies that Europeans will not have access to.”

The letter concluded with a call for “harmonized, consistent, quick and clear decisions under EU data regulations that enable European data to be used in AI training for the benefit of Europeans.”

The signatories stressed the situation’s urgency.

“Decisive action is needed to help unlock the creativity, ingenuity and entrepreneurialism that will ensure Europe’s prosperity, growth and technical leadership.”

The EU’s regulatory landscape has become increasingly complex, with new rules like the General Data Protection Regulation (GDPR) and the upcoming AI Act adding layers of compliance for businesses.

Cecilia Bonefeld-Dahl, director general of DigitalEurope, told DW that smaller companies are particularly burdened, facing what she called a “tsunami” of overregulation. Many startups, including several valued at over $1 billion, are relocating to the United States due to the prohibitive costs of staying in Europe.

Industry leaders argue that Europe’s regulatory environment is forcing local companies to fall behind global competitors, particularly in the U.S. and China, where AI innovation is surging ahead in less restrictive markets.

New York Lawmakers Consider AI Regulations

New York state legislators are exploring new AI regulations to address worries about privacy, copyright and potential deception.

During a Friday (Sept. 20) assembly hearing, lawmakers and the state attorney general expressed concerns about fraud and other negative consequences of unchecked AI. Chief Deputy Attorney General Chris D’Angelo emphasized the need for transparency:

“We think that the companies that put out AI models that generate this content need to also have an obligation to watermark that content so that people can hold them accountable and trace it back,” D’Angelo said, per a Saturday (Sept. 21) Times Union report.

The state has taken initial steps to promote AI, with Gov. Kathy Hochul announcing a $275 million Empire AI Consortium project, the report said. However, regulations have lagged behind technological advancements.

Assemblyman Alex Bores highlighted worries about open-source AI potentially being used to generate dangerous information, according to the report. Meanwhile, industry representatives like IBM’s Roslyn Docktor urged lawmakers to focus on regulating risk rather than core algorithms.

“AI is a tool, and like any tool, it can be misused…,” Docktor said, per the report. “But we do not regulate the underlying tools — we regulate how they are used in different contexts.”

Appian CEO Demands IP Safeguards

Appian CEO Matt Calkins is advocating for more substantial intellectual property (IP) protections as AI regulations struggle to keep up with technological advancements, particularly around data source disclosures and privacy, CIO Dive reported Wednesday (Sept. 25).

“We don’t talk nearly enough about the AI intrusion on personal privacy and private information intellectual property,” Calkins said, per the report.

He said he is working with U.S. lawmakers to push for rules requiring AI models to disclose their data sources, obtain consent for using private or copyrighted data, and ensure anonymization of personal information, the report said.

Calkins and industry leaders like ScienceLogic CEO David Link said they believe transparency in AI data use is essential for building trust, according to the report. However, the lack of clear regulations has heightened legal risks for enterprises, especially concerning IP.

Calkins emphasized that maintaining trust between companies and customers is vital as AI becomes more integrated into business operations, the report said. Without proper governance, businesses face challenges navigating the AI landscape while safeguarding IP.

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The company announced two updated production-ready models in a Tuesday (Sept. 24) blog post, Gemini-1.5-Pro-002 and Gemini-1.5-Flash-002, which offer enhanced capabilities across a range of tasks, including product recommendations, inventory management and customer service automation.

“The new release introduces advanced capabilities in math and vision tasks,” Sujan Abraham, a senior software engineer at AI firm Labelbox, told PYMNTS. “These models are designed for a wide range of tasks, including text, code and multimodal applications. They can process larger and much more complex inputs like 1,000-page PDFs, massive code repos and hour-long videos. These models are faster, better and more cost-efficient for production environments.”

Price Cuts and Performance Boost

In a move likely to intensify competition in the AI market, Google is reducing pricing for its Gemini-1.5-Pro model by more than 50% for both input and output on prompts under 128,000 tokens. The company is also doubling rate limits for the 1.5 Flash model and tripling them for 1.5 Pro.

“To make it even easier for developers to build with Gemini, we are increasing the paid tier rate limits for 1.5 Flash to 2,000 RPM and increasing 1.5 Pro to 1,000 RPM, up from 1,000 and 360, respectively,” the post stated.

Performance improvements are up, with Google reporting an approximate 7% increase in scores on the MMLU-Pro benchmark, which measures general knowledge and reasoning abilities. Both models showed a “considerable ~20% improvement” on math-related benchmarks, according to the post.

“The Gemini 1.5 series is more efficient across the board,” Jorge Argota, founder of an AI consultancy, told PYMNTS. “These models are text, code and multimodal. When dealing with complex math or code, they are more understanding and accurate. This could be a game changer for eCommerce platforms looking to implement advanced AI features.”

Argota highlighted the extended context window as a significant advancement.

“The models can now process up to 2 million tokens, which is a big jump from previous versions,” he said. “This means they can handle long documents and multimedia inputs with ease. For projects with large datasets or long documents, this is a huge win.”

New Features 

The updates also address speed and efficiency concerns.

“Along with core improvements to our latest models, over the last few weeks we have driven down the latency with 1.5 Flash and significantly increased the output tokens per second, enabling new use cases with our most powerful models,” Google’s blog post said.

Argota noted several key new features, including “Gems, personalized AI assistants,” which allows users to create custom AI assistants for specific tasks. He also mentioned the Imagen 3 model, “an advanced image generation model that produces higher quality images from text prompts,” and Gemini Live, which enhances conversational AI interactions through voice conversations.

The price reductions and increased rate limits are expected to impact businesses.

“The 15% price drop and increased rate limits is a big win for businesses looking to add AI to their workflows,” Argota said. “The cost savings makes these advanced models more affordable, especially for startups and small businesses that were hesitant to get in due to budget constraints.”

Google’s push to make its AI models more attractive to developers comes as competition in the sector intensifies, with rivals like OpenAI and Anthropic also vying for market share.

The company is betting that these improvements will encourage more developers to build applications using Gemini, potentially leading to broader adoption of Google’s AI technologies.

“We continue to be blown away with the creative and useful applications of Gemini 1.5 Pro’s 2 million token long context window and multimodal capabilities,” the blog post said. “From video understanding to processing 1,000-page PDFs, there are so many new use cases still to be built.”

In addition to the production models, Google is releasing an experimental version called “Gemini-1.5-Flash-8B-Exp-0924,” which the post said includes “significant performance increases across both text and multimodal use cases.”

The updates also include changes to the models’ default filter settings, giving developers more control over content moderation.

“For the models released today, the filters will not be applied by default so that developers can determine the configuration best suited for their use case,” the post said.

As the AI arms race continues, Google’s latest move signals its commitment to remaining competitive in a rapidly evolving market. With these enhancements, the company aims to solidify its position as a provider of AI tools for developers and businesses.

“Overall, a big win for businesses looking to add AI to their workflows,” Argota said.

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Google and Sabre’s AI innovations offer personalized experiences and increased revenue, while destinations like Richmond, British Columbia, deploy AI assistants to enhance visitor engagement, reflecting a broader trend reshaping how we plan and experience travel.

Google, Sabre Unveil AI-Driven Travel Innovations

Google and Sabre are using AI to personalize and streamline consumer experiences, according to a Monday (Sept. 23) post by WiT.

Four years into a strategic partnership, the companies unveiled their latest developments at a virtual event. The innovations harness AI and generative AI to address the growing consumer demand for tailored travel services.

Sundar Narasimhan, senior vice president of labs technology and platform at Sabre, cited industry estimates projecting AI could generate over $28 billion in global travel revenue. Seventy-four percent of travel organizations are revising their strategies to incorporate AI, he said, according to the post.

Robust data sets are key to effective AI implementation, he added, per the post.

Among the prototypes showcased was SynXis Booking Engine Concierge.AI, a tool for hoteliers that offers personalized guest recommendations. Another, Travel Email IQ, automates the process of reading customer emails and generating customized travel suggestions.

Sabre is using Google’s Vertex AI platform to optimize airline pricing and product merchandising. Early results show that Air Price IQ, one of Sabre’s AI-powered solutions, has demonstrated a 3% increase in airfare revenue for airlines, the post said.

Sabre is focusing on generative AI for future hospitality solutions, said Amy Read, vice president of innovation at Sabre Hospitality, per the post, adding that AI is “the future” of travel.

Richmond, British Columbia, Deploys AI to Boost Tourism Experience

Richmond, British Columbia, is the latest destination to sign onto an AI virtual travel assistant powered by Matador Network, Travel and Tour World reported this month.

Tourism Richmond introduced AskLulu, an AI tool developed in collaboration with Matador Network’s GuideGeek technology. The tool aims to enhance visitor engagement and streamline travel planning.

AskLulu, accessible through Tourism Richmond’s digital platforms, offers real-time, personalized information to travelers. The AI assistant draws from an extensive database curated by Tourism Richmond and over 1,000 integrations from GuideGeek to provide detailed responses on local attractions, dining options and accommodations.

The move reflects a growing trend in the travel industry, as AI tool adoption surged 40% over the past year. Richmond’s initiative positions it at the forefront of this technological shift in Canadian tourism, potentially setting a new standard for digital visitor services.

The deployment of AI in tourism is wider than in Richmond. Other destination marketing organizations, including Travel Manitoba, have implemented similar technologies, per the report. Internationally, tourism boards in Europe and North America, such as Greece, Aruba, and Reno-Tahoe, are also using Matador Network’s GuideGeek technology.

AI Travel Startup Mindtrip Raises $12 Million

Mindtrip, an AI-powered travel planning platform, secured $12 million in funding from Forerunner Ventures and existing investor Costanoa, PhocusWire reported this month.

The company plans to use the capital to expand operations and develop new collaborative trip-planning features.

The software company also launched a group chat feature on its platform. The tool allows multiple travelers to discuss plans, share preferences and receive AI-generated suggestions during the planning process.

“We believe every trip should be as delightful to plan as it is to experience…,” Mindtrip co-founder and CEO Andy Moss said in the report.

The company’s focus on group travel is informed by internal research indicating that 90% of people travel with at least one companion, and 73% primarily travel with family, the report said. Mindtrip aims to address the challenges of coordinating preferences among multiple travelers.

The platform uses AI to combine individual preferences into a single itinerary. Users can modify plans and access chat history within the interface.

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Bahrain’s push to integrate AI into its economic vision, national security infrastructure and workforce development is part of a rapidly growing movement across the Middle East. AI has become a central focus as countries in the region race to diversify their economies and establish themselves as tech hubs.

Bahrain’s comprehensive AI strategy exemplifies the Middle East and North Africa (MENA) region’s ambitions. A study suggested it could be a model for wider AI adoption in the area.

“The rise of AI-driven eCommerce platforms can significantly expand the retail sector, facilitating access to global markets for local businesses,” geopolitical analyst Irina Tsukerman, president of Scarab Rising, told PYMNTS. “This boosts domestic production and consumption, reducing dependency on oil revenues.”

AI Boom in the Middle East

Bahrain’s FinTech sector sits at the heart of its AI ambitions. The country has already established itself as a FinTech hub in MENA, using its strategic location and business-friendly regulations to attract innovators from across the globe.

The Central Bank of Bahrain is trying to encourage AI adoption in the financial sector. It has issued directives on digital finance advice and established a regulatory sandbox where FinTech startups can test innovative AI-powered solutions in a controlled environment.

Bahrain’s AI aspirations extend beyond finance. The country is also integrating AI into its national security framework, joining an international working group on the safe use of AI in the military. In partnership with the United States, Bahrain will lead efforts to develop guidelines for implementing AI in defense applications.

Bahrain is also using AI capabilities in maritime security. In collaboration with United Kingdom-based SRT Marine Systems, the country has implemented AI-powered surveillance systems to monitor its coastal waters, creating what the company described as a protective barrier around the island nation.

Regional Competition Heats Up

Other Middle Eastern nations are in the AI race.

MGX, a United Arab Emirates state-backed tech investment company, is considering joining a multibillion-dollar funding round for OpenAI that could value the AI firm at $150 billion. The move aligns with the UAE’s broader strategy to position itself as a global AI hub, using its substantial sovereign wealth to reduce dependence on oil revenues.

A $40 billion AI investment fund from Saudi Arabia signals a seismic shift in the Middle East’s tech landscape. By 2030, the Middle East could capture 2% of AI’s total global benefits, amounting to approximately $320 billion.

The UAE has unveiled an AI strategy to position the country as a global leader in AI by 2031. Saudi Arabia is investing billions of dollars in AI research and development as part of its Vision 2030 plan to diversify its economy.

“The current data center capacities in Saudi Arabia and the UAE are approximately 123 megawatts and 235 megawatts, respectively, lower than those of many European countries,” Tsukerman told PYMNTS. “Saudi Arabia is currently the fastest-growing data center market, with a projected total capacity of 854 megawatts by 2029.”

The impact of AI extends beyond the technology sector.

“AI is already having a transforming effect on many of the traditional industries in the Middle East,” Tsukerman explained. “AI-enhanced seismic data interpretation helps identify hidden resources and optimize drilling in the oil and gas sector.”

In finance, she said, “Chatbots and virtual assistants provide 24/7 customer support, improving client engagement and reducing operational costs for banks. AI tools assess risk by analyzing vast datasets, enabling banks to make informed lending decisions and manage investment portfolios more effectively.”

The race for AI dominance in the Middle East extends beyond the UAE and Saudi Arabia, Ilya Smirnov, head of the AI/ML Department at Usetech, told PYMNTS.

“Slightly less influential, but still notable, are Oman, Bahrain, Qatar and Kuwait,” he said, adding these nations are implementing comprehensive strategies to boost their AI capabilities.

AI’s potential in the region spans multiple sectors.

“AI has great potential for development in the Middle East…,” Smirnov said. “All of this allows the region to stand out in the market and transform many industries with new technologies.”

He cited a specific example from the energy sector, where AI has been used to tackle production challenges.

“As part of this, our company has developed a resource consumption model based on a decision support and decision-making system,” he said. “It allows us to reduce fuel consumption by up to 5% per day and improve the quality of product output.”

The AI revolution also brings challenges.

“Where many of the Middle Eastern states gain in resources and engagement, they lack in local skillset and thorough understanding of ethical, legal and other issues around the AI framework, which will likely delay advancements in many of the areas and cause setbacks in others,” Tsukerman said.

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From self-driving cars navigating city streets to smartphones instantly translating foreign languages, AI is increasingly moving out of centralized data centers and onto the devices we use daily. This shift toward “edge AI” represents a significant evolution in how AI is deployed and used, promising faster response times, improved privacy and the ability to operate in environments with limited connectivity.

Edge AI computing brings AI capabilities directly to devices and local networks rather than relying on distant cloud servers. This allows for faster processing, reduced latency and improved privacy since data doesn’t need to travel far from where it’s collected and used.

The impact on commerce could be particularly profound. Retailers are experimenting with AI-powered cameras and sensors to create cashierless stores, where customers can simply pick up items and walk out, with payment processed automatically. Online shopping could become more personalized, with AI-enabled devices offering real-time recommendations based on a user’s behavior and preferences. Smart shelves with embedded AI could dynamically adjust pricing based on demand and inventory levels in brick-and-mortar stores, potentially revolutionizing traditional retail strategies.

The Rise of AI at the Edge

Edge computing isn’t a new concept, but its marriage with AI is opening up possibilities that were once the realm of science fiction. By processing data locally on devices rather than sending it to the cloud, edge AI can reduce latency from seconds to milliseconds, improve privacy by keeping sensitive data on the device and operate in environments with limited or no internet connectivity.

One prominent application is in autonomous vehicles. Tesla’s Full Self-Driving computer, powered by a custom AI chip, can process 2,300 frames per second from the car’s cameras, making split-second decisions crucial for safe navigation. This local processing allows Tesla vehicles to operate even in areas with poor cellular coverage, a critical feature for the widespread adoption of self-driving technology.

In our pockets, smartphones can increasingly run complex AI models locally. This on-device processing speeds up these features and enhances user privacy by keeping personal data off the cloud.

Google’s latest Pixel phone showcases the power of on-device AI with features like Live Translate, which can translate speech in real time without an internet connection. The Pixel’s custom Tensor chip can process natural language at a rate of 600 words per minute, a capability that would have required a server farm just a few years ago.

The true potential of edge AI may lie in its ability to transform entire cities. In Singapore, a network of AI-enabled cameras and sensors is being deployed as part of a “Smart Nation” initiative. These devices can monitor everything from traffic flow to public safety, processing data locally to respond to incidents in real-time while minimizing the transmission of sensitive information.

Despite its potential, the rise of edge AI is challenging. Hardware limitations mean edge devices often can’t run the most advanced AI models. This has led to a race among chipmakers to develop more robust, energy-efficient AI processors. Nvidia’s Jetson line of AI computers can deliver up to 275 trillion operations per second while consuming as little as 5 watts of power, making them suitable for a wide range of edge devices.

The proliferation of AI-enabled devices raises questions about surveillance and data ownership. The growing number of decisions AI makes at the edge necessitates increased transparency and accountability in these systems.

The Future of AI at the Edge

The momentum behind edge AI shows no signs of slowing. In healthcare, companies like Medtronic are developing AI-enabled insulin pumps that can monitor blood glucose levels and adjust insulin delivery automatically, potentially revolutionizing diabetes management.

Nvidia’s Clara AGX AI computing platform enables AI-powered medical devices to process high-resolution medical imaging data locally, speeding up diagnoses and improving patient privacy.

In agriculture, John Deere’s See & Spray technology uses onboard AI to distinguish between crops and weeds, allowing for precise herbicide application and potentially reducing chemical use by up to 90%.

Edge AI will continue to evolve, and we can expect to see even more innovative applications emerge. The possibilities are vast, from smart homes that can predict and respond to our needs to industrial equipment that can self-diagnose and prevent failures before they occur.

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The Chinese tech company’s expansion in generative AI aims to provide businesses with new tools for customer engagement and content creation in online retail and marketing. The move could democratize access to advanced AI tools, particularly benefiting small- to medium-sized businesses (SMBs).

“Large tech incumbents, whether Alibaba or Meta, are playing the age-old game of commoditizing your complement,” Mike Conover, CEO of AI company Brightwave, told PYMNTS. “By creating a robust development ecosystem around technologies that enhance their core offerings, such as product marketplaces or messaging, these firms increase their differentiated value and talent brand in a competitive hiring environment.”

The release could lower barriers for businesses, especially SMBs, to adopt advanced AI tools in eCommerce and digital marketing. This democratization of AI access may lead to more personalized customer experiences, innovative product showcases and efficient operations across the global retail landscape, potentially reshaping how companies compete and engage consumers in the digital marketplace.

Open-Source Surge

Alibaba’s open-source AI strategy allows global users to create generative AI applications without the costly process of training their systems. This approach has led to 40 million downloads of their models since the launch of Tongyi Qianwen (Qwen) last year, according to a company blog post.

Alongside open-source offerings, Alibaba upgraded its proprietary Qwen-Max model, claiming similar performance as competitors like Meta’s Llama and OpenAI’s GPT4 in reasoning and language comprehension, per the post. The company also introduced a text-to-video tool like OpenAI’s Sora, expanding its AI capabilities. The multi-pronged approach aims to increase Alibaba’s AI user base and enhance its position in the global AI market.

“Open-source AI large models have the potential to significantly impact global commerce and trade by democratizing access to advanced AI tools, reducing barriers for businesses of all sizes to leverage AI,” Pundi X co-CEO Peko Wan told PYMNTS. “[SMBs] will benefit from reduced costs, allowing them to leverage AI for innovation and competitiveness.”

Wan also pointed out potential benefits for Alibaba.

“Alibaba can attract a broader user base, encouraging businesses to adopt their cloud infrastructure for hosting and scaling AI solutions, thereby driving increased demand for their paid cloud services like storage, computing power and data management,” Wan said.

The tech industry has seen a trend of open-source AI. These publicly accessible tools offer a range of capabilities, from solving complex mathematical problems to writing code and translating between 29 languages, the post said.

Industry experts point out that this approach, also adopted by other tech giants, reshapes the AI landscape. Meta’s Llama, for instance, has been widely used for natural language processing tasks, while Google’s BERT has become a cornerstone for many text analysis applications.

By making these AI models freely available, companies enable a broader range of users to develop AI applications. A small eCommerce startup, for example, could use these models to create a chatbot for customer service or an automated product recommendation system. Similarly, researchers in fields like climate science or genomics could use these tools for data analysis without needing extensive AI expertise or resources.

The democratization of AI technology is expected to accelerate innovation across various sectors. In healthcare, open-source models could be adapted for tasks like medical image analysis or drug discovery. In finance, they might be used to enhance fraud detection systems or automate risk assessments.

Global AI Impact

As AI increasingly influences eCommerce, Alibaba’s move may prompt competitors to reconsider their AI strategies and could shift how companies approach digital sales and advertising globally. The long-term impact on international commerce could be significant, with Wan suggesting it may “foster greater collaboration across borders, breaking down traditional barriers in international trade and creating more dynamic, interconnected global markets.”

Thanks to cheaper open-source models, smaller businesses and startups could access sophisticated AI capabilities, enabling them to compete more effectively with larger players in the eCommerce space.

Swapnil Sawant, a software developer at Phoenix Bioinformatics, told PYMNTS: “With basic AI capabilities now openly accessible, competition will shift toward how effectively eCommerce companies can integrate and customize these models, as well as the development of more advanced, specialized AI applications with better UX integrated with AI enhancing online shopping further. The global adoption of these models may spark discussions about data privacy and digital sovereignty, potentially influencing international trade policies and regulations.”

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Nvidia’s AI Aerial Takes Flight

Nvidia’s new AI Aerial platform is shaking up the telecom industry, promising to transform cellular networks into smart systems that could change eCommerce and supply chains.

By infusing AI into radio access network technology, the platform aims to optimize wireless networks, potentially accelerating the deployment of next-gen tech like 5G, robotics and autonomous vehicles while boosting eCommerce with enhanced recommendation engines and dynamic pricing models.

HubSpot’s ‘Breeze’ AI Blows In

HubSpot’s new AI-powered platform Breeze is making waves in the marketing tech world, offering a suite of tools designed to streamline content creation, social media management and customer service.

As digital channels become increasingly saturated, the move reflects a broader industry shift toward AI integration, with the promise of more personalized campaigns, improved data analysis and enhanced customer experiences across fragmented digital landscapes.

AI’s Retail Makeover

Forget futuristic robots. AI’s true retail impact is happening behind the scenes.

From predicting customer desires to slashing customs paperwork, embedded AI is transforming commerce with practical solutions. Experts say these smart systems are already streamlining supply chains, personalizing customer experiences and automating tedious tasks, promising a new era of efficiency and innovation in retail and logistics without sci-fi fanfare.

Tech Giants Bet $100 Billion on AI-Powered Data Centers

A new alliance of industry heavyweights, including Microsoft and BlackRock, is wagering $100 billion on AI’s future, aiming to build a network of cutting-edge data centers.

The push could redefine global trade, supercharging everything from supply chains to financial services. With promises of lightning-fast transactions, hyper-personalized shopping experiences and smarter resource management, these AI hubs may soon become the invisible backbone of a more efficient and responsive commercial landscape.

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In a speech drafted for delivery at StepChange Connected 2024 in Leeds, Rathi cited this as an example of how regulators must consider both the risks and the benefits of AI and other technology when promoting financial inclusion.

“We want safe and responsible use of AI to drive beneficial innovation,” Rathi said. “But also an open conversation about the risks and trade-offs.”

Other examples of technology risks include the privacy concerns associated with better data sharing and the recent controversy around the dynamic pricing used in a sale of Oasis concert tickets, Rathi said.

Digital inclusion can also promote financial inclusion, Rathi said. He cited as examples the efforts of Finexos to increase the availability of affordable credit, the work of Noggin to produce an alternative credit score for consumers with limited credit history, and a report from an unnamed FinTech that anonymous chatbots providing debt advice benefit consumers by reducing the stigma associated with debt.

“Do we accept that the risk of a few experiments failing or some people not benefiting from innovation is outweighed by the potential benefit to the majority of consumers and long-term growth and productivity improvements?” Rathi said. “I freely admit that we don’t yet have full estimates of the benefits of inclusion to growth and productivity. But experience elsewhere suggests that resolving foundational issues could have big impacts.”

Rathi suggested that financial inclusion can be promoted by improving financial literacy, enhancing digital literacy and inclusion, embracing digitalization and technological innovation, and “being more ready to experiment and take some measured risk to deliver better long-term economic outcomes.”

It was reported in June that financial services companies have been slow to embrace AI products because of regulatory concerns and worries about job losses.

In another report, the Bank for International Settlements said in June that the financial sector is among the “most exposed” to both the benefits and the risks of AI. The benefits of AI for the sector include improvements to lending and payments, while the risks include more sophisticated cyberattacks.

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The new VoiceX platform is designed to deliver a more human-like intelligent conversational experience than traditional voice bots that often sound robotic, struggle with limited conversational depth and context, and respond slowly, the company said in a Tuesday (Sept. 17) press release emailed to PYMNTS.

“Latency and lack of coherence have been a major challenge, causing high abandonment rates and frustrating customer experiences,” Yellow.ai CEO and co-founder Raghu Ravinutala said in the release. “The demand from enterprise customers was evident — this gap needed to be addressed. With VoiceX, we’ve made significant strides, empowering enterprises to deliver natural, fluid interactions with the speed of machines, ultimately enhancing the overall customer experience.”

VoiceX is engineered to enable natural, uninterrupted conversations; deliver accurate responses to intricate and detailed queries; provide relevant responses based on user history and preferences; promote engaging interactions by acknowledging, empathizing and encouraging users to continue speaking; and ensure clear conversations by canceling out background noise, according to the release.

The voice platform integrates with customer relationship management (CRM) systems and enterprise knowledge bases, connecting smoothly and enabling easy escalation to human agents when needed, per the release.

“We developed VoiceX by rethinking our technology stack and implementing massive parallelization of services for optimal orchestration,” Rashid Khan, chief product officer and co-founder of Yellow.ai, said in the release. “For example, VoiceX is deeply integrated with our YellowG ecosystem, providing enterprises with access to our suite of [large language models]. These [models] power various functions of customer service automation, dynamically invoked based on the nature of the query and the required action.”

Advances in conversational AI-powered dynamic AI agents have expanded their language capabilities, enabling them to streamline operations and cut costs for multinational corporations with global call centers, Ravinutala told PYMNTS in an interview posted in August.

“Voice AI can detect and respond in multiple languages, while generative AI chatbots engage in nuanced multilingual conversations, enabling human-like conversations with empathy and clarity,” Ravinutala said.

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