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New Survey from Harvard Business Review Analytic Services Finds AI Adoption Remains High, Yet Value May Lag Without Modernization and Workflow Integration

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A critical AI success gap is emerging for organizations, with 30% surveyed seeing an impact on new revenue streams.

ORLANDO, Fla., April 30, 2026 /PRNewswire/ — Most organizations have moved beyond experimenting with artificial intelligence, but few are realizing its full value. New research from Harvard Business Review Analytic Services, sponsored by Appian, finds that while 59% of organizations (who are moving forward with AI to some extent) have AI in production, the majority are currently focused on incremental gains that prioritize efficiency and productivity over top-line growth.

Notably, AI has the strongest impact in bolstering productivity, not enabling growth. Respondents indicated that of the AI performance measures their organization tracks, most see impact in productivity improvements (64%) and operational efficiency (58%), while metrics like new revenue streams (30%) and ROI (35%) are among the least likely to have improved. This points to a significant opportunity for organizations to use AI to deliver broader business outcomes and growth.

“Enterprises are at an inflection point. Instead of using AI to drive productivity, organizations must evolve to focus on business growth. That’s where Appian comes in,” said Matt Calkins, CEO of Appian. “The true potential of AI can only be realized when it moves from a standalone tool to an embedded worker that drives revenue. To get there, leaders must prioritize the foundational orchestration and rules-based guardrails required to safely apply AI to high-impact work.”

AI still sits outside the flow of work

In most organizations, AI is being used alongside work, not built into how work gets done, limiting its ability to drive higher-level business outcomes. Only 18% of respondents report that AI is primarily integrated within workflows, while a larger share (34%) continue to use AI as standalone tools alongside processes/workflows, with another 34% reporting a mix of both approaches and 12% not yet using AI in processes/workflows at all.

Most see some returns on AI, but not yet at scale 

Most respondents are seeing some returns from AI investments, but only 16% report realizing a high degree of measurable value. The majority describe the impact as moderate (33%), slight (36%), or have no measurable value (8%). Still, expectations remain high, as 86% agree that their organization is looking to realize more business value from its use of AI. It’s clear that AI is delivering some results, but translating those results into meaningful, scalable business impact is proving difficult.

AI delivers value when embedded in workflows

As organizations advance their AI strategies, value is closely tied to how effectively AI is integrated into workflows and applied to operational work. Seventy-one percent of organizations embedding AI into processes realized substantial or moderate value from those efforts, according to respondents. In parallel, approximately three-quarters report strong returns from modernizing legacy infrastructure/systems (76%), integrating data sources (75%), and orchestrating processes/workflows across systems/applications (73%).

Legacy systems continue to limit AI’s impact

Nearly seven in ten respondents, 69%, agree that legacy systems are limiting their ability to scale AI across the enterprise. This reinforces the need for modernization and better integration across systems and data. Siloed or low-quality data (34%), a lack of integration across systems (31%), and a lack of AI talent/skills (30%) are also among the most commonly cited barriers to embedding AI into workflows.

AI agent adoption lags in core operations

The research also highlights differences in how AI agents are being applied across the enterprise. Organizations are more actively deploying AI agents in areas such as software development (35%), IT operations (31%), marketing and sales (26%), and customer service (25%). In contrast, agent adoption is more limited in core operational areas such as procurement (9%), manufacturing (10%), and supply chain (11%), where processes tend to be more complex and require greater control and consistency. As organizations look to expand AI into these environments, governance becomes critical.

Most organizations lack the guardrails needed to scale AI agents safely

Ninety-two percent of respondents agree that AI agents need rules-based guardrails to operate safely and effectively, yet fewer than half (48%) agree that their organization has defined such rules (among those at organizations using, considering or exploring agentic AI). As organizations explore agentic AI systems (currently used by 25% of organizations and under consideration by 62%), the need for clearly defined processes and guardrails will become even more critical. Without clear guardrails, agents can act unpredictably across systems, increasing the risk of unintended outcomes.

Process design is emerging as the key to unlocking AI value

Realizing the full value of AI and achieving sustainable ROI requires rethinking how work is structured and governed. According to respondents, organizations are increasingly focused on better defining rules/guardrails that AI must follow (50%), standardizing processes/workflows across functions (49%), and increasing cross-functional coordination (47%) to improve the success of AI implementations.

“Organizations are adopting AI, but many haven’t integrated it into the core processes that drive business outcomes,” said Alex Clemente, managing director of Harvard Business Review Analytic Services. “Those that successfully embed AI into workflows will be better positioned to realize meaningful value.”

Read the full study. 

About the Research

In March 2026, Harvard Business Review Analytic Services, sponsored by Appian, surveyed 385 business decision makers from organizations that are exploring, piloting, or actively using artificial intelligence (AI).

About Appian

Appian provides process automation technology. We automate complex processes in large enterprises and governments. Our platform is known for its unique reliability and scale. We’ve been automating processes for 25 years and understand enterprise operations like no one else. For more information, visit appian.com. [Nasdaq: APPN]

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Ally Waste Acquires Swift Integrated Services, Expanding Service Capabilities and Market Reach

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GILBERT, Ariz., Sept. 3, 2026 /PRNewswire/ — Ally Waste, a nationwide provider of comprehensive waste solutions for multifamily communities, announced today that it has acquired Swift Integrated Services, a Utah-based provider of dumpster management, doorstep trash pickup, and waste brokerage services.

“Every acquisition we make starts with the same question: Will it help us serve customers better? Swift expands our reach and brings capabilities that allow us to support more of our customers’ waste needs. We’re excited to welcome the Swift team to Ally and build on what they’ve created,” said James Crawley, CEO of Ally Waste.

The acquisition expands Ally Waste’s presence in Utah, Florida, and Idaho markets while strengthening the company’s waste stream optimization capabilities. It also brings waste brokerage capabilities to Ally, giving current customers another way to address their waste needs as the offering is integrated.

“Joining Ally gives us the opportunity to build on what we’ve created while bringing our customers the support and resources of a nationwide team,” said Indigo Schumann-Curtis, President of Swift Integrated Services. “Our customers can expect business as usual, with many of the same people continuing to support them. I’m excited about what our teams can accomplish together.”

Swift Integrated Services customers can expect continuity in both service and support throughout the transition. The Swift team will continue with Ally, bringing established customer relationships and deep market knowledge to the combined organization.

About Ally Waste

Ally Waste is a nationwide provider of comprehensive waste solutions for multifamily communities, including valet trash and recycling, bulk removal, and waste stream optimization services. Its technology gives owners and operators clear visibility into what they’re paying for waste across a portfolio, paired with on-the-ground teams who put those insights into action.

The company’s culture is grounded in its values of Integrity, Grit, and Humility. These principles drive Ally Waste’s commitment to supporting multifamily teams and delivering consistent, high-quality service that improves everyday life for residents and on-site staff. Learn more at www.allywaste.com.

Media Contact:
Doridé Uvaldo
duvaldo@allywaste.com

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SOURCE Ally Waste

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Gupshup Launches Self-Serve Voice AI Platform, Extending Conversational Engagement into Phone Calls

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Businesses can now build, test, and deploy AI voice agents across support, sales, and operations – alongside WhatsApp, RCS, and SMS – from a single platform

MUMBAI, India and SAN FRANCISCO, Sept. 3, 2026 /PRNewswire/ — Gupshup launched its Voice AI Platform, a self-serve console for building and running AI voice agents that handle calls end to end. The launch extends Gupshup’s engagement platform from messaging into voice, bringing support, sales, and operations onto the same infrastructure businesses use for WhatsApp, RCS, and SMS.

Gupshup’s Voice AI Platform resolves support calls, qualifies and converts leads, and automates operational calls such as scheduling, verification, and payment reminders, so human teams can focus on conversations that require a person.

The platform covers agent lifecycle in a no-code, prompt-based interface. Businesses configure an agent’s voice, language, knowledge base, system prompt, and workflows, then connect it to tools their teams use. Before going live, teams define guardrails, run simulations, and validate behaviour with tests – comparing models. Once deployed, analytics track success rates, satisfaction, and language usage, with transcripts, conversation history, and debug logs for review.

Gupshup’s platform is the first to bring unique capabilities. First, voice is a channel extension of a platform serving businesses across WhatsApp, RCS, and SMS – enabling voice-and-messaging experiences within a customer journey. Second, it supports telephony: PSTN and WhatsApp voice channels, on-premise and cloud deployment, and the option to bring PSTN infrastructure. Third, it is model-flexible – businesses choose speech-to-text, text-to-speech, and LLM providers rather than accepting a stack.

The platform builds on Gupshup’s experience powering customer engagement for 50,000+ businesses across 100+ countries and 25+ industries, processing 10 billion interactions monthly, including 500 million voice calls per month.

The Voice AI Platform has been beta tested and delivered outcomes across deployments. Users receive 100 minutes of credits to test, and pricing starts at USD 0.035 (INR 3.50) per minute.

“For customer engagement in emerging markets, Voice AI drives universal access – reaching every user regardless of language or literacy. In developed markets, it drives efficiency and automation. In both, it delivers cost savings, revenue growth, and satisfaction. With the launch of its Voice AI Platform alongside its messaging, Gupshup offers the only unified self-serve platform for customer engagement across voice and messaging,” said Beerud Sheth, Co-founder and CEO, Gupshup.

The Voice AI Platform is available to businesses at voiceai.gupshup.io.

For more information, visit www.gupshup.ai.

 

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SOURCE Gupshup Technology India Pvt Ltd

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Deepdub Launches Phantom Z 3.4 Conversational: Multilingual Text-to-Speech Built to Survive Real Customers, Not Just Demos

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Enterprise-grade real-time text-to-speech delivers 150ms time to first audio at full 48 kHz, with text normalization that gets account numbers, invoice totals and appointment dates right

TEL AVIV, Israel, Sept. 3, 2026 /PRNewswire/ — Deepdub, a foundational voice AI company pioneering expressive voice technologies, announced today the launch of Phantom Z 3.4 Conversational, a new multilingual text-to-speech model with high-fidelity 48 kHz audio, improved text normalization and extended Hebrew support. The model is available to all Deepdub clients now.

For enterprises running voice agents, a call holds together when four things go right at once. The voice sounds like a person. The response arrives fast enough to feel like a conversation. The agent knows when to speak and when to listen. And every account number, date and amount comes out the way a customer would say it. When one of them slips, the call escalates to a human, and that is where containment and cost are decided. Phantom Z 3.4 Conversational is built for all four.

“Every voice model sounds impressive for two minutes in a demo. Very few survive two weeks with real customers,” said Ofir Krakowski, CEO and co-founder of Deepdub. “Deployments don’t stall on the 95% a model gets right, they stall on the misread account number, the mangled surname, the one wrong digit on a live call. We built this model for that last few percent, because in production, the last few percent is the whole product.”

In English, the work is in text normalization, the step that turns written text into spoken words. A delivery date written 2024-12-31 is read as December thirty first, twenty twenty-four rather than as a run of digits. An invoice total written $1,240 is read as one thousand two hundred forty dollars. An appointment at 14:30 is read as two thirty. A reference written Chapter VII is read as chapter seven rather than as letters. These are the categories where Deepdub’s testing puts the model ahead of the other systems it was measured against. An enterprise running more than one language gets one set of behavior to test and one contract to hold rather than two.

Phantom Z 3.4 delivers an end-to-end p95 time-to-first-audio of 150 milliseconds in real-time mode at full-range 48 kHz audio, with cross-language voice transfer from under three seconds of reference audio. Deepdub builds and trains its own speech models from random rather than licensing them, which allows the company to bring a new language into production in two weeks. Deepdub covers more than fifty locales and dialects verified by local voice and language experts, inside a platform supporting more than 50 locales and dialects.

“We run Deepdub in production for live, real-time phone calls, where latency and naturalness aren’t nice-to-haves but the key factor in whether a caller stays on the line. 3.4 is the closest we’ve heard a synthetic voice come to a real person, and our callers show it: they stay longer, talk more, and engage with our agents like we’ve never seen before,” said Adir Haziza, CTO at Voiceman.

The hardest case is Hebrew, which is written without vowels, so the same letters can spell different words. The three letters of שלט are a sign read one way and a remote control read another. A model that reads one word at a time has to guess which the sentence means, and in Hebrew a wrong guess is not an accent, it is a different word that stays invisible until a customer hears it. Phantom Z 3.4 resolves this at the source. Pronunciation is decided from the whole sentence rather than word by word, and every instance of שלט in Deepdub’s Hebrew test set was read correctly. Where a brand name or a plan tier has to be said a particular way, marking it in the text is enough. Deepdub ranks first for Hebrew text-to-speech on the public TTS Arena leaderboard hosted by ivrit.ai on Hugging Face.

In Hebrew, national ID numbers, appointment dates and transaction amounts are expanded before speech, so a balance written as 1,240 ₪ is spoken in full rather than read out as digits. In blind listening tests, Phantom Z 3.4 was preferred over Deepdub’s previous Hebrew model in 71 percent of decisive comparisons.

“We needed something that would hold up consistently across a large volume of work, so we tested it thoroughly before deciding. What stood out was that the details came out right and the Hebrew was the most natural we’d heard,” said Dor Levy, Head of Jeen Talk at Jeen AI.

About Deepdub
Deepdub is the foundational voice AI model company pioneering expressive voice technologies for global enterprises across TV, film, advertising, gaming, e-learning, and AI-agent applications. The company’s international team of technology, dubbing, and linguistic experts deliver an end-to-end voice solution that preserves the emotional and cultural integrity of original content in more than 50 locales and dialects. With an advisory board that includes media leaders such as Kevin Reilly, former Chief Content Officer at HBO Max, and Emiliano Calemzuk, former President of Fox Television Studios, Deepdub is eliminating language barriers to enable the global diffusion of media on major streaming platforms like Netflix, Amazon Prime, and Hulu. Visit https://deepdub.ai or follow us on LinkedIn for more information.

Deepdub Media Contact
Zivit Katz
Deepdub
zivit.katz@deepdub.ai

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SOURCE Deepdub

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