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Arab News
3 days ago
- Business
- Arab News
Deloitte Middle East advances AI integration with launch of Global Agentic Network
Deloitte has launched its Global Agentic Network, a strategic initiative designed to scale AI-driven digital workforce solutions for organizations around the world, with significant potential to transform business operations across the Middle East. As AI adoption accelerates in the region, Deloitte's agentic AI offering provides a future-forward solution that combines intelligent automation with human expertise. Through its global network spanning EMEA, Asia Pacific, and North America — and with a growing regional focus in the GCC — Deloitte is bringing AI-powered agents to enterprises looking to drive operational efficiency, accelerate growth, and reimagine how work gets done. Agentic AI refers to software agents capable of autonomously executing tasks, orchestrating workflows, and adapting based on input from users or other systems. These agents, powered by large language models and machine learning, are designed to learn and evolve — making them ideal for complex, dynamic business environments. In the Middle East, where government and private sector agendas alike are emphasizing digital transformation, the Global Agentic Network supports national strategies for AI innovation and economic diversification. Deloitte is already supporting regional clients in sectors such as energy, government, and financial services to implement agentic solutions that streamline decision-making, improve efficiency, and unlock value at scale. 'The Middle East is on a rapid trajectory toward AI-led transformation, and Agentic AI is a game-changer for how businesses operate,' said Yousef Barkawie, Deloitte Middle East Gen AI leader. 'At Deloitte, we're helping our clients navigate the world of AI transformation by architecting and building the capabilities and trust needed for them to scale out their AI deployments and transform at the core. Our clients are finding new efficiencies in their ways of working, streamlining their operations, and reimagining their entire value chains. This is an exciting moment to help shape what the future of work looks like in our region, especially as governments and industries double down on innovation and future-readiness.' The Global Agentic Network includes alliances with leading technology platforms and the launch of solutions like Zora AI, Deloitte's suite of proprietary AI agents that can autonomously perform complex business functions. These tools are already being deployed within Deloitte's own operations, as part of the firm's broader ambition to become an AI-fueled organization by 2030.
Forbes
10-06-2025
- Health
- Forbes
AI Agents Are Coming To Healthcare
A digital workforce is coming to healthcare. getty Y Combinator calls 2025 the 'year of AI agents,' and singled out healthcare as a key focus area. Bill Gates predicts that agents will 'upend the software industry, bringing about the biggest revolution in computing since we went from typing commands to tapping on icons." Nvidia CEO Jensen Huang recently proclaimed that agents "present a trillion-dollar opportunity.' You get the point. Agents are all the rage throughout the tech industry. But what exactly are agents? What role might they play in healthcare? And what's holding them back from realizing their potential? Because early chatbots used decision trees and scripted responses, they struggled with in-depth conversations. With ChatGPT's release, millions of people discovered how to interact with large language models across an almost unlimited range of topics. Agents build on that foundation. They are LLMs enhanced with capabilities such as retrieval, memory, and tools—enabling them to carry out narrowly defined tasks without human supervision (e.g., booking a flight or responding to a customer service request). While copilots assist humans, agents take over tasks entirely. Agentic AI coordinates multiple task-specific agents to accomplish multi-step goals. Many healthcare provider organizations are struggling. Their workforces are strained and shorthanded. Margins are thin, labor costs are rising, and many processes are inefficient and wasteful. Meanwhile, patients often struggle to access timely, affordable, and effective care. Numerous industries, such as banking, travel, and personal finance, have improved productivity and service by doing more with fewer people. Agents may unlock similar opportunities in healthcare. Always on, scalable, and tireless, agents could automate a range of administrative and even clinical processes. That's why many view agents not just as tech, but as operational infrastructure and digital labor. As Luminai CEO Kesava Kirupa Dinakaran explained, 'When you think about how computers can drive value, it's by improving operations. At their core, healthcare organizations are all about operations.' The hope is that agents can expand access, lower costs, improve experiences, and enhance outcomes. A burgeoning wave of companies is racing to deliver AI agents that enable provider organizations to do more with less. Call centers are today's leading use case. Most patients still make appointments by phone, and many skip them due to scheduling hassles. Agents can manage inbound calls by conversing with patients and taking the next best actions (e.g., scheduling an appointment or making a referral). When agents cannot handle an end-to-end call, they can verify key details, summarize the conversations, and hand off to human staff. Assort Health Co-CEO Jeff Liu explained that his company aims to help healthcare organizations 'train the best operators they ever had.' By turning scheduling protocols into rules engines and plugging agents into EHRs, his co-CEO Jon Wang reported that their company automates most inbound calls—routing the rest to call center workers and nurses in priority order. Similarly, Hello Patient CEO Alex Cohen reports that his company's 'fully generative voice and SMS agents handle real-time front‑office calls and proactively re-engage patients, letting clinics boost access and fill schedules without adding headcount.' Agents are also handling outbound calls. Notable's agents prepare patients for clinic visits by verifying their insurance benefits, clarifying (and documenting) their reason for the visit, and checking them in for their appointments. Qventus' agents help optimize patients for procedures and surgeries by providing preparation instructions, sending appointment reminders, answering general care questions, and coordinating pre-admission testing. Infinitus deploys agents to perform health risk assessments and help patients access specialty therapies and rare disease programs. Some agents support patients between and after visits. Ambience Healthcare is developing agents that send follow-up instructions, medication reminders, and scheduling prompts based on visit notes. Hippocratic AI provides a constellation of agents for nurse-level clinical tasks, such as making post-discharge follow-up calls and closing care gaps. The company calls this 'super staffing' since many organizations lack the staff to do enough of this work on their own. Sword Health, a digital physical therapy platform, uses agents to onboard patients, provide customer service, and even help them return hardware. And Cedar recently launched an AI voice agent, Kora, to handle billing inquiries, explain charges, surface payment options, and connect patients with financial assistance. Agents are not limited to patient-facing roles—they're also streamlining the back office. For example, one of Luminai's agents reads incoming faxes and automatically triggers downstream workflows like refills and referrals. VoiceCare AI automates communication between provider organizations, insurers, and patients. Its CEO, Parag Jhaveri, reported that their agent, Joy, can wait on hold for more than 30 minutes, navigate phone trees, sustain multi-hour conversations, and take actions like updating claims and filing requests. Building a well-scripted, polished demo is easy. Delivering reliable performance on real-world healthcare tasks is much harder. Agents often score far short of human performance. For one, healthcare is complex—filled with edge cases, exceptions, and contextual nuance. As legendary software engineer Steven Sinofsky noted, automation is ultimately about handling exceptions, not the routine. Several technical barriers stand in the way. Healthcare data is deeply siloed and fragmented. Lisa Bari, Head of External Affairs at Innovaccer, warns against deploying agents without full contextual data. Also, while LLMs enable agents to handle a wide range of inputs, they can produce uncontrolled outputs. Longer conversations and more contextual data can reduce accuracy and increase latency. Moreover, error rates compound across multi-step processes. For example, an agent with 98% per step will complete a five-step task successfully only 90% of the time (0.98⁵). Developers use various strategies to make agents more reliable. As Sword Health product lead Rik Renard, RN, emphasized, "Evaluating agents' output against pre-specified criteria is essential for deploying reliable agents, yet few people discuss this.' Many agentic systems use specialized knowledge graphs to contextualize information and 'coordinating agents' to link multiple, narrow task-specific agents. Technical guardrails help ensure agents stay within scope and flag questionable output for human review. Still, picking the right use cases is critical. Notable Chief Medical Officer Dr. Aaron Neinstein told me that his company first deploys agents in low-risk areas (e.g., patient intake) to build trust before expanding into more complex workflows. Even with clear use cases, deployment remains hard and no shortcuts exist. As Cedar CEO Dr. Florian Otto summed it up, 'Agents must be built workflow by workflow and only deployed when they reliably work well.' Agents must also integrate with other tech systems—like EHRs and CRMs—to access contextual data and execute tasks. Most use native API integrations, though some interact through the same point-and-click interfaces that healthcare workers use. Ultimately, in an 'agentic economy,' agents must interact with one another—communicating information, transferring resources, collaborating, and tracking transactions. This will require persistent identity and seamless communication protocols, which developers are now building. Several companies, including Salesforce, Microsoft, and Innovaccer, have launched platforms to orchestrate multi-agent healthcare workflows. "Any sufficiently advanced technology is indistinguishable from magic.' Arthur C. Clark famously explained, "Any sufficiently advanced technology is indistinguishable from magic.' If you haven't interacted with an AI agent or tried a modern voice model, you should. This isn't your mother's old pharmacy's IVR system. The technology has crossed the uncanny valley — it feels like magic. But unlike magic, it's not infallible. In high-stakes situations, unreliable AI can cause real harm. As extreme examples, consider how the National Eating Disorder Association's chatbot 'Tessa' encouraged users with eating disorders to diet, or how a companion allegedly pushed a teenager to commit suicide. Agents, however, are more than chatbots. They are tireless digital workers who are always ready to complete specific tasks. When stitched together, they can form multi-agent systems—or 'agent swarms'— that handle complex, interdependent processes and behaviors. Yet, US and EU regulators have approved exceedingly few healthcare AI agents. Hardian Health's Dr. Hugh Harvey warns, "Health systems and clinicians using unregulated AI agents must accept all the risk.' Will they be willing? While regulatory approval is cumbersome, it may be necessary to speed adoption. Also, unlike magic, AI agents aren't plug-and-play. Implementing agents is a massive change-management undertaking. Patients will need to adjust their expectations and learn to interact differently with technology and healthcare. In his book Alchemy, Rory Sutherland explains that in our 'unrelenting quest' for greater efficiency, we often forget to ask 'whether people like efficiency as much as economic theory believes they do.' Take the 'doorman fallacy:' a hotel that replaces doormen with automatic doors may save money, while overlooking the other valuable functions doormen provide, such as hailing taxis, providing security, welcoming guests, and signaling the hotel's status. Similarly, healthcare workers often do far more than their simple job description. For example, if agents automate scheduling, who will reassuringly mention that 'everyone loves Dr. Smith' or that she tends to run late at the end of the day? Of course, healthcare workers aren't perfect or always available. Several company leaders I spoke with say patients prefer interacting with their agents over healthcare workers. But this remains to be seen. Outside healthcare, Klarna—the buy now, pay later company—recently walked back its ambitious efforts to replace two-thirds of its customer service workforce with AI agents. It turns out many customers still want to talk to real people. Agents will also reshape how healthcare workers do their jobs. By offloading drudgery, agents could empower some. Yet others may resent having to babysit new digital coworkers that could potentially replace them. Interestingly, one company CEO shared that executives and managers–not frontline staff–are often the most resistant. Perhaps they worry agents will shrink their teams and reduce their influence. Or, more likely, they may feel daunted by all that responsible deployment demands: surfacing tacit knowledge, defining ground truths, streamlining workflows, and retraining workers for new forms of human-AI collaboration. Infinitus CEO Ankit Jain explained his company 'sells outcomes, not technology.' It focuses on supporting change management, recognizing that 'organizations must be able to crawl before they walk and then run.' For agents to succeed, organizations must look inward. Technology is an amplifier. It can boost productivity or magnify inefficiency. Healthcare organizations, which strongly pull towards inertia, must actively reexamine their operations, rebalance their workforces, and reinforce their digital governance. Otherwise, poorly integrated agents could cause confusion and chaos. Optimizing workflows is essential. So is relieving downstream constraints. For example, a flawless appointment-scheduling agent is of limited value if doctors' schedules are always full. An outreach agent that flags patient needs is only helpful if there are enough nurses and clinicians available to respond. Taken together, these developments point toward a future that's both promising and uncertain. 'Technology is neither good nor bad; nor is it neutral.' Healthcare's digital history has taught us hard lessons: technology can help, but it cannot miraculously solve all problems. And tech doesn't work in isolation—lasting change depends on rethinking people, processes, and priorities, not just deploying tools. Roy Amara famously observed, 'We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.' That seems likely with AI agents. In the near term, agents will make existing workflows faster and cheaper—answering calls, managing intake, and making appointments. Next, they may improve those workflows—coordinating across channels, adding personalization, and responding with context. Eventually, they may enable entirely new approaches, with networks of agents operating semi-autonomously across systems. At the heart of this evolution is a core tension: leverage versus certainty. Agents promise a kind of abundance—tireless labor at negligible cost. But that leverage introduces risk. For now, they'll likely remain in administrative domains, where errors are less costly and rarely dangerous. Still, care delivery is also quite inefficient. Care models for both acute and chronic illness have barely changed in decades—and the clinician-patient encounter remains healthcare's choke point. Here, too, agents may help: handling triage, guiding protocol-driven decisions, even managing chronic conditions. Much of this is already technically feasible. But real progress will require much more: rigorous evaluation, regulatory clarity, updated business models, cultural acceptance, redesigned teams, and seamless escalation paths to human care. Melvin Kranzberg's First Law reminds us: 'Technology is neither good nor bad; nor is it neutral.' The promise of agents is real—but conditional. Their impact depends on how we design, deploy, and govern them. Will agents make care more personalized—or more transactional? Will they return time to clinicians—or reduce their autonomy and turn them into machine supervisors? Will they bring people closer together—or insert more distance? Will they relieve burden—or hollow out the human core of care? Agents are coming. What they become depends on us. I thank the following people for discussing this topic with me: Ray Chen and Jonathan Fullerton (Ambience Healthcare), Jeffery Liu and Jon Wang (Assort Health), Florian Otto (Cedar), Hugh Harvey (Hardian Health), Alex Cohen (HelloPatient), Rick Keating (Hippocratic AI), Ankit Jain (Infinitus), Abhinav Shashank and Lisa Bari (Innovaccer), Pankaj Gore (Insight Health), Kesava Kirupa Dinakaran (Luminai), Aaron Neinstein and Tushar Garg (Notable), David Atashroo (Qventus), Rouhaan Shahpurwala ( Rik Renard and Kevin Wong (Sword Health), Maria Gonzalez Manso (Tucuvi), Parag Jhaveri (VoiceCare AI), Sergei Polevikov (WellAI), and Stuart Winter-Tear.
Forbes
03-06-2025
- Business
- Forbes
How To Future-Proof Your Career At Age 45 And Stay Competitive
Mid-career professionals are embracing upskilling and digital tools to stay relevant in today's ... More digital workforce. Your forties arrive faster than expected. One moment, you're the rising voice in the room; the next, you're planning for retirement while navigating a workplace that increasingly amplifies the perspectives of recent graduates. If you're 45 and questioning how to keep up in a job market that seems to shift by the minute, you're not the only one. What worked in your 30s may now feel outdated. On the positive side, your career isn't winding down; it's evolving. The employment rate for the 45-54 age group is consistently high, reflecting a large and stable segment of the workforce, according to Statista. However, unemployed individuals 45 and older face ageism. You must be intentional about staying visible and maintaining their value. Staying relevant requires an ongoing strategy that evolves with your industry, not against it. By age 45, many professionals face growing pressure to adapt to digital transformation and generational shifts in the workplace. According to the Harvard Business Review, age-diverse teams lead to stronger innovation and performance. But experience alone won't keep you competitive. Platforms like Coursera, LinkedIn Learning and edX offer short, accessible certifications specifically designed for mid-career professionals. A career pivot doesn't require starting from scratch; it requires a strategic rebrand. Update your LinkedIn profile with a clear headline that aligns with your future goals, not just past roles. Share posts or insights that position you as a thought leader. Use AI tools like Resume Worded or Teal HQ to audit your LinkedIn for keyword strength and tone. Staying competitive at 45 means combining experience with adaptability, balancing what you've ... More mastered with a willingness to grow. Instead of just aiming higher on the corporate ladder, seek roles that flex your expertise while helping you grow. These include: If you've considered launching a business, your mid-40s are the best time to do it. MIT Sloan found that entrepreneurs aged 40-60 statistically build more sustainable companies than younger founders. Offer mentorship while remaining open to new approaches. Reverse mentoring is a powerful way to stay agile and informed across generations. Future-proofing your career is a continuous process. The mindset shift involves replacing 'I've done this before' with 'What can I learn next?' Chasing every trend is exhausting; you'll burn yourself out. Staying aligned with what the future of work in your sector demands focus. Stay adaptable, not anchored. The job market may be changing, but your ability to adapt gives you a distinct edge. Make your move before it passes you by; step into it with intention. The professionals who thrive at 45 and beyond are boldly building what's next.
The Australian
02-06-2025
- Business
- The Australian
Rise of the digital workforce: rethinking work in the age of agentic AI
What is perceived as science fiction today becomes mainstream tomorrow – and transformative the day after. Such is the progression of generative AI, and now, agentic AI. We may not have all the answers yet. But the questions are becoming clearer. And the organisations that ask them early – and act boldly – will shape the future of work for the better. As Professor Ethan Mollick said recently, 'The time to begin isn't when everything becomes clear – it's now, while everything is still messy and uncertain. The advantage goes to those willing to learn fastest.' The pace at which AI is evolving is staggering. Agentic AI – autonomous systems capable of reasoning, learning, and acting independently – are no longer a theoretical concept. Agents are already executing human tasks, orchestrating workflows, and adapting through interactions with both humans and other agents. It's only getting faster as enterprise software players, hyperscalers, platform providers, frontier labs and new agentic product start-ups are innovating and releasing capabilities into market at a blistering pace. The short of it really is that we've well and truly entered a new era of transformation – and what we're witnessing is the rise of a digital workforce. To harness its full potential, we must move beyond outdated paradigms – especially the one-to-one thinking that equates digital labour to human labour in direct substitution. Human capacity is finite. Digital labour is not. It's a limitless, scalable, always-on capacity that can multiply effort, insight, and creativity at a scale and speed that previously was not possible. When we break this outdated paradigm, and rethink how we work, the opportunities look very different. Stu Scotis, National GenAI Lead at Deloitte Australia Picture a marketing team empowered by AI agents capable of simulating hundreds of thousands of campaigns, then surfacing the top-performing strategies for a human to evaluate. Or a sales force supported by thousands of virtual assistants, each tailoring offers to individual customer profiles based on real-time analysis of preferences, history, and behaviour. Or a finance team where CFOs have thousands of digital finance analysts. These examples are just a starting point, and exciting as they are, even these are constrained by today's thinking of structure and work. We're not just talking about automation for productivity – it's a reinvention of how we work. It demands a wholesale redesign of how we think about workflows, roles, and even how value is created. This is happening now and if you're following this space closely, you'll have seen headlines with high-profile CEOs setting directives on AI usage by employees with AI first strategies. We're also seeing examples of even bolder moves with some organisations merging HR and IT departments as the line between managing technology and managing people becomes increasingly blurred with agents. These organisations are going beyond surface-level integration and not just bolting AI onto existing systems – they are reimagining those systems entirely. They are looking at core functions such as customer service, product development, HR, and operations to be restructured and redesigned to take full advantage of AI's capabilities. Looking ahead, leadership roles also need to be redesigned as we consider the digital workforce. To date, leadership has been built around managing people, now we need managers who orchestrate fleets of AI agents as well as human teams. Setting clear expectations, evaluating outputs, and defining what 'good' looks like are quickly becoming core competencies for leaders as they take on accountability to transform their organisations with AI. Another essential question for every organisation is this: how far will you allow automation to proliferate? The capability is here – but are your systems, culture and people prepared? Agentic AI can perform complex tasks end-to-end, but without clear governance and ethical guidelines, it can introduce real risk. The path forward involves deliberate decisions about where to retain human oversight, where to build in safeguards, and how to ensure transparency in automated processes. What the end state looks like when functions, organisations or even sectors are redesigned around AI is not yet clear. But waiting isn't an option. Those who progress the fastest will gain significant, if not impassable, competitive advantage. We might not want to be in a race with AI – but we are. It's a global race, and the stakes are high. Productivity, competitiveness and economic growth are all on the line. And as the pace of technological change accelerates, so must our ability to act with clarity and intent. The race leaders will be those who are already laying the groundwork to rebuild, rethink and reinvent around AI. We've got a lot more to say about how organisations should be planning to shape the future of work with a sustained focus on delivering scale and value. Watch this space! Stu Scotis is National GenAI Lead at Deloitte Australia. - Disclaimer This publication contains general information only and Deloitte is not, by means of this publication, rendering accounting, business, financial, investment, legal, tax, or other professional advice or services. This publication is not a substitute for such professional advice or services, nor should it be used as a basis for any decision or action that may affect your business. Before making any decision or taking any action that may affect your business, you should consult a qualified professional advisor. Deloitte shall not be responsible for any loss sustained by any person who relies on this publication. About Deloitte Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited, a UK private company limited by guarantee ('DTTL'), its network of member firms, and their related entities. DTTL and each of its member firms are legally separate and independent entities. Please see to learn more. Copyright © 2025 Deloitte Development LLC. All rights reserved. -
