Latest news with #agenticAI
Forbes
an hour ago
- Business
- Forbes
Cutting Costs, Driving Progress: Evolving Your Organization With Agentic AI
President of TELUS Digital Solutions at TELUS Digital, a company dedicated to crafting unique and enduring digital customer experiences. Artificial intelligence (AI) is rapidly moving past generative AI (GenAI) tools like ChatGPT, DALL-E and Gemini toward genuine autonomy. Google, OpenAI and Nvidia are among major technology companies that have recently announced expansions of agentic AI capability. These moves are prompting enterprise leaders across all sectors to consider—and prepare for—a future with agentic AI. By definition, agentic AI has agency or autonomy to make decisions, plan and execute complex, end-to-end tasks. It takes the gains of GenAI, which generates human-like content, into new territory. By automating process optimization and resource allocation, agentic AI's autonomous decision-making capabilities present significant opportunities for businesses to reduce costs through efficiency gains. Future-forward brands looking to harness the true power of AI to achieve business goals and put themselves on the leading edge are already taking note: • A Statista survey commissioned by my firm, TELUS Digital, found more than a third (36%) of businesses plan to allocate more than $4 million apiece to GenAI initiatives in 2025. • Deloitte predicts that 25% of companies currently using GenAI will launch agentic AI pilots or proofs of concept this year, growing to 50% by 2027. • KPMG's survey of 252 business leaders found more than half (57%) plan to invest in or adopt agentic AI in the next six months and a third (34%) plan to within the next 12 months. Even if a brand isn't equipped to take this next step, those looking to remain competitive in the long term should be readying their organizations to meet this transformative moment by laying the groundwork now. The AI Ecosystem: Combining GenAI And Agentic Capabilities GenAI assistants and similar foundational applications have allowed enterprises to create content and software at scale—as the name implies, these tools are focused on generation, namely through creating text, images and code. We've also seen GenAI streamline work processes, boost productivity, enhance search tools across large, complex data repositories and augment multimodal voice AI applications. Many of the models behind these advancements are essentially supercharged chat interfaces that rely on human prompts, instructions and back-and-forth conversations. A core difference of agentic AI is that humans set the goals and the AI assistant decides how to approach the task. In the finance industry, for example: • A GenAI assistant may respond to a customer's or agent's request to change the payment due date on a credit card with step-by-step instructions and a link. • An agentic AI assistant, however, could autonomously analyze a customer's financial profile (spending patterns and account history) and identify and enact cross-selling opportunities. It could proactively initiate a personalized offer, such as a travel rewards credit card with no foreign transaction fees based on observed international spending patterns, complete with pre-calculated savings and a pre-approval application. This autonomous approach could significantly reduce customer acquisition costs while increasing conversion rates through more efficient, targeted engagement. Taking The Next Steps With Agentic AI As enterprises look to expand their AI capabilities from GenAI to include agentic AI, leaders must assess their readiness in terms of both organizational structure and technological infrastructure. Preparing your organization for agentic AI requires both cultural transformation and structured implementation planning. Success depends on fostering a culture of continuous learning, where employees develop new technical and soft skills through accessible training opportunities. Building on this foundation, organizational readiness may include: • Cross-departmental alignment: Establish clear goals and success metrics for your agentic AI strategy across all departments, ensuring measurements reflect both departmental needs and broader organizational objectives. • Strategic prototyping: Identify an initial agentic AI use case with clean, accessible data for proof of concept. Define clear boundaries and limitations to manage expectations and maintain focused development efforts. • Prioritizing use cases: Create an inventory of potential use cases across departments based on business impact, technical feasibility and implementation complexity to develop a phased implementation road map for scaling agentic AI across the organization. • Documenting and assessing workflows: Nothing is more counterproductive than automating a poor workflow, so use this time to document and reassess the workflows themselves. • Establishing governance frameworks: Implement clear ethical guidelines and oversight mechanisms, including a human-in-the-loop approach and regular audits, to ensure agentic AI aligns with organizational values throughout its deployment and scaling. Assessing your organization's AI capabilities is another key stage for agentic AI readiness. At TELUS Digital, we use the AI maturity curve as a framework to understand how advanced or integrated the use of AI is, from early experimentation to full-scale strategic development. Organizations should aim for a point on the curve where AI is being deployed across business functions before proceeding. To assess your technological readiness: 1. List every AI or machine learning project underway—even those still in the early concepting stages—and the data that flows into these systems. 2. Review your tech stack, data integration systems and processing capabilities to ensure they can support agentic AI requirements. 3. Assess your data governance frameworks and quality control processes to confirm they can support autonomous decision-making. 4. Identify and prioritize gaps in your current technical infrastructure that could impact agentic AI implementation, focusing on your highest-priority use cases. This dual focus on organizational and technological readiness ensures a strategic approach to agentic AI adoption that balances innovation with practical implementation. Understand The Future To Prepare For It As enterprises explore how agentic AI can complement their GenAI capabilities, the potential for cost reduction becomes increasingly clear. While GenAI has already demonstrated efficiency gains, agentic AI's capabilities promise even greater savings by independently executing complex tasks and proactively identifying optimization opportunities. However, it's crucial to recognize that agentic AI is one piece of a broader, interconnected AI ecosystem, and its full impact on various industries is still unfolding. The key to realizing agentic AI's potential lies in thoughtful preparation and implementation. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Forbes
4 hours ago
- Business
- Forbes
How Agentic AI Is Reshaping Consumer Marketing—And How To Navigate It
Richard Jones is Chief Revenue Officer of Wunderkind, helping brands adapt to modern trends amid any ever-evolving customer landscape. We're witnessing the most significant marketing transformation since the rise of mobile. Only this time it's powered not by a new channel but by a new intelligence: agentic AI. Unlike traditional generative AI tools, which respond to human prompts, agentic AI operates autonomously. It observes, learns, reasons and executes. In short, it acts. And it's not a theoretical promise. It's happening right now. I've watched this evolve firsthand at Wunderkind, where we use agentic AI as the foundation of our autonomous marketing platform. I've seen how it adapts to consumer behavior in real time, recommends strategies and triggers personalized messages in ways that don't just improve marketing campaigns, but completely reinvent them. The brands thriving in today's high-stakes market are using autonomous marketing platforms to convert behavioral chaos into conversion precision, especially during critical sales windows like Black Friday/Cyber Monday (BFCM). Here's what you need to know to lead, not lag, in the new marketing paradigm. Agentic AI is your new navigator, not just an assistant. Generative AI helps create. Agentic AI helps decide. And in an e-commerce environment where consumers are more calculated, cautious and cost-conscious than ever, those decisions matter. This is where agentic AI can help. We all know that consumers will switch brands for better prices. But price alone isn't enough to win. Winning requires the right message at the right time in the right channel. Agentic AI in a marketing technology platform can leverage trillions of real-time behavioral signals—scroll depth, bounce timing, cart contents—and cross-reference them with economic trends to determine not just what to say, but when, where and why. For example, say a customer—let's call him Robert—is browsing jackets on his phone, but pauses for several seconds on a product page without adding anything to his cart. He scrolls back twice, checks shipping info and then exits. Meanwhile, your agentic-AI-powered platform references two critical factors about the interaction: First, Robert previously abandoned a cart and only converted after receiving a time-sensitive discount. Second, tariff-driven price increases in the outerwear category have spiked 15%, making shoppers more hesitant to commit without clear value. Using this context, the platform determines that Robert should receive a mobile push notification within 15 minutes, offering free shipping and a limited-time loyalty reward, emphasizing product durability and inflation protection. The message is delivered at 8:45 p.m., his historical peak engagement window. The result? Robert re-engages, converts and adds gloves to his order thanks to a bundled offer suggested by the same AI system based on his purchase patterns. This isn't just marketing. This is micro-orchestrated intelligence in motion—and at scale. Identity is the secret weapon; AI makes it explosive. Agentic AI is only as effective as the data it ingests. And nothing fuels smarter decisions like identity resolution. When you can identify visitors without requiring a login, and fuse that with historical behavioral data, you can turn bounce-prone browsers into high-value buyers. The result is a cross-channel flywheel where emails are personalized in real time, text messages are hit during peak conversion windows, onsite overlays adapt to user behavior and redundancy is suppressed across devices and platforms. Leading retailers, publishers and travel platforms are also leveraging identity resolution in similar ways, using known user profiles to deliver coordinated messaging across web, mobile, email and even call centers, creating a seamless customer experience. AI isn't just automating touchpoints. It's curating journeys. AI kills 'spray and pray' marketing for good. Consumer behavior during BFCM 2024 delivered some unmistakable messages: Mobile-first is no longer optional, and urgency is meaningless without relevance. Yes, 'ends at midnight' still spikes conversions, but only when combined with personalized triggers rooted in identity and behavior. That's where agentic AI shines. It understands when a user is browsing multiple tabs looking for the best deal (as we found 40% of consumers are), when a Gen-Z shopper needs reassurance on price, or when to convert interest into urgency through SMS before a cart is abandoned. What used to be static journeys are now dynamic conversations led by AI that learns from every signal. Incorporate agentic AI into your Black Friday/Cyber Monday planning. BFCM is more than a seasonal sprint. It's a high-stakes expedition. In today's tariff-inflated, loyalty-fractured environment, half of consumers now delay nonessential purchases until BFCM, treating it like a strategic chess match. This is where agentic AI proves its worth. Last year, we found that 33% of BFCM revenue on our platform was driven by known users through hyper-personalized, behavior-based messaging. These weren't generic blast emails. They were real-time decisions based on session depth, previous purchases and contextual urgency. Every shopper got the message they needed—no more, no less. The biggest opportunity for marketers isn't just winning Q4. It's using the insights, lists and behavior from BFCM to power always-on, performance-driven growth. To stay ahead in this agentic AI-driven era, marketers should: • Invest in training. Equip teams with the skills to work alongside AI agents effectively. • Ensure data integrity. Maintain high-quality, unified data to feed AI systems accurately. • Implement ethical guidelines. Establish frameworks to govern AI decision making processes. • Foster collaboration. Encourage cross-functional teams to integrate AI insights into broader business strategies. By embracing agentic AI thoughtfully, marketers can unlock new levels of efficiency and personalization, driving deeper consumer engagement and loyalty. But despite the capabilities of agentic AI, human oversight remains crucial. Human taste and craftsmanship are essential to distinguish meaningful content from AI-generated material. Marketers must ensure that AI-driven strategies align with brand values and resonate emotionally with consumers. The brands that win are the ones that let AI lead. We're not in the era of creative-first marketing anymore. We're in the era of calculated experience. AI doesn't just assist. It agents. And that shift is seismic. Whether navigating the volatility of BFCM or scaling sustainable growth in a cost-conscious economy, the brands that succeed in 2025 and beyond will be those that let AI reason, decide and deploy while marketers steer the strategic course. Autonomy isn't a luxury anymore. It's survival. And with agentic AI, it's your advantage. Forbes Business Development Council is an invitation-only community for sales and biz dev executives. Do I qualify?
The Verge
a day ago
- Business
- The Verge
I asked Alexa Plus to tackle my to-do list — it mostly failed
One of the best features of Amazon's new Alexa Plus is that I don't have to 'speak Alexa' anymore. I've been testing the voice assistant for about a week now, and it understands what I say, regardless of how I say it — there's no more need for precise phrasing to get Alexa to do what I want. This big shift underpins another headline feature of the revamped generative AI-powered assistant that I've been testing: agentic AI. But this one needs work. The idea is I can talk to Alexa Plus as I would to a real personal assistant and ask it to do tasks, such as reserving a restaurant for my friend's birthday, finding an electrician to fix my broken sprinkler pump, or booking tickets to a Chris Isaak concert. The assistant can then act as an 'AI agent' and navigate online services on my behalf to book everything for me. Combined with better calendar management and the ability to remember things you tell it, Alexa's agentic AI has the potential to make the assistant much more useful. Alexa's AI agent features are neither broad enough nor seamless enough to replace my real-life personal assistant: me At least in theory. In reality, it's too limited. Alexa Plus relies on partnerships with specific services; it can't just roam the web and do my bidding. As of now, that includes Ticketmaster, OpenTable, Uber, and Thumbtack. While impressively, Alexa did manage to complete several steps, overall, the AI agent's current features are neither broad enough nor seamless enough to replace my real-life personal assistant: me. Alexa Plus is still in an Early Access beta phase, and Amazon says more integrations are coming soon. These include ordering groceries by voice (via 'several grocery providers in the US'), delivery through Grubhub, and booking spa visits through Vagaro. These may be more useful to me, especially grocery ordering. I already use Alexa for my shopping list, but I then have to put everything into my Harris Teeter shopping app for pickup or delivery. If Alexa could take that list and add it to a service like Instacart, it would cut out a chunk of work for me. Of the three agentic experiences I tested, the best was booking a ticket to an event through Ticketmaster. After a dodgy start — when I asked about sports events and was told about a youth basketball training session — I tried again. 'What events are there in Charleston next month that you can buy me tickets for?' Alexa produced a list of about 10 local sports events and concerts on the Echo Show 15 I was using (Alexa Plus is much more useful on a screened device). It told me, 'You've got music shows like Blackberry Smoke and Mike Campbell on August 5th and Collective Soul on August 6th. There's also a Cure tribute band on August 2nd. Anything catch your interest?' I spotted a Chris Isaak concert in the list (I love a good Wicked Game) and told it to book me tickets. It found balcony seats for $98.15 each and asked how many I wanted, while also showing me more expensive options. I selected the cheap seats, and it walked me through each step as it added them to my cart, ending with a checkout button where my credit card details were pre-populated. (I'd linked my Ticketmaster account in the Alexa app when I first set up Alexa Plus.) I canceled before purchasing, because I don't love a Wicked Game $200 much, and Alexa confirmed that the tickets were released. However, alarmingly, later that day, a pop-up in the Alexa app told me that anyone with access to my Alexa devices can order tickets. Amazon: I'll take a PIN option here, please. Next, I asked Alexa to 'book a dinner for two in downtown Charleston for tomorrow night at 7PM.' It returned three options, which is just sad — Charleston has a hopping foodie scene. I picked a French spot I'd been to before and changed it up, asking Alexa to 'make it for two weeks on Friday.' Unfazed, Alexa understood, pivoted and confirmed availability for Friday, July 31st, at 7PM, then asked if I wanted to book. After I confirmed, it said it would also add the reservation to my linked Gmail calendar. Handy! Alexa had messed up the date Or so I thought. I then received a text message from OpenTable, confirming my reservation for Thursday, July 31st. Alexa had messed up the date. I told Alexa to switch the reservation to Friday, August 1st, and it did, also updating my calendar. While it eventually booked the table, Alexa took longer to do it and was less accurate than if I'd just opened the OpenTable app on my phone (or more realistically, the Resy app that most restaurants in Charleston use) and done it myself. Finally, I had Alexa tackle a chore I've been putting off for two years: finding an electrician. I've been meaning to get the circuit for my sprinkler pump fixed for ages. It's on the same one as my internet router, so when the pump kicks in, it trips the circuit — and down goes my Wi-Fi. The big difference is that I did all of this hands-free I told Alexa I needed an electrician to fix the sprinkler system, and asked if it could book one. It pulled a list of several 'highly rated electricians' in my area via Thumbtack, highlighting the top three. I picked one and asked it to schedule a visit for a week from now. Alexa asked several follow-up questions about my house and the specific issue — it felt a bit like filling out a webform with my voice. Alexa, then said it was working on sending the request through the Thumbtack website, and that I'd get updates soon. A few hours later, still no word from Alexa. But I received an email from Thumbtack (the first of many…) and a text message from the electrician asking me to call or text to schedule an appointment. Not exactly the seamless set-it-and-forget-it experience I'd hoped for. Still, the big difference is that I did all of this hands-free. I could be setting up dinner dates and finding electricians while cooking dinner or folding laundry. As a working mother of two, anything that helps with multitasking so I can complete my to-do list faster is welcome. But while the tech is impressive, the lack of depth and the failures I experienced in two out of my three tests mean I don't plan to rely on Alexa to do these tasks for me just yet. Photography by Jennifer Pattison Tuohy / The Verge
Fast Company
3 days ago
- Business
- Fast Company
From hype to humanity: Driving more value with human-centered AI
In boardrooms and backroom labs, the promise of AI has morphed into modern mythology—a digital elixir promising to revolutionize industries and workforces, eliminate inefficiency, and empower businesses and humans like never before. As investments increase and headlines dominate, we find ourselves swept up in a collective fever dream—a hype cycle where AI is the universal solution to our most significant problems. According to Forrester's AI research, 67% of AI decision-makers say their organization plans to increase AI investment. With the advent of agentic AI, there seems to be even more enthusiasm about implementing it. In a June 2025 press release, Gartner reported that a poll of 3,400 IT professionals revealed that 19% said that their organization had made significant investments in agentic AI, 42% reported conservative investments, 8% had made no investments, and the remaining 31% were unsure about agentic AI investments in their organization. Beneath the hype lies a more sobering reality. Gartner analysts also predicted that 40% of agentic AI projects will be cancelled by 2027 due to costs, unclear business value, or inadequate controls. At Punchcut, we've led companies through several pivotal moments in tech evolution to achieve meaningful ROI. Our latest report, FutureView 2025: From Hype to Humanity, examines the gap between unrealistic AI expectations and results. It's a guide to ensure real drivers of revenue and profit, user satisfaction, and competitive advantage define AI initiatives. The AI revolution isn't solely about groundbreaking technology; it's fundamentally about shaping more profound and useful connections between humans and machines. By grounding AI work in human-centric principles, product teams can craft experiences that break free from the hype and deliver genuine, lasting benefits. A central insight from our work with business leaders is that AI objectives defined by human-centered needs deliver the strongest results. Real value hinges on AI's ability to enrich personal and professional activities and enable human potential. Amidst the frenzy, companies must move from hype to reality to pragmatically steer projects toward human-centered implementations. Only then will it drive loyalty and ultimate revenue growth. FOUR PRINCIPLES OF HIGH-VALUE AI Through our work, we've identified four key AI strategies for successful AI initiatives. AI implementations that follow these 'lanes' can deliver measurable returns rapidly while producing sustainable business benefits. 1. SHARED AUTONOMY The idea of completely autonomous systems is intriguing, but most users desire a feeling of control. Our findings indicate that people prefer a collaborative approach where autonomy is shared between humans and machines. Recently, we worked with a global automotive company to build an advanced in-vehicle AI agent for assisted driving. Primary testing revealed a strong preference for optional agent support over full automation. Drivers felt much more comfortable with the ability to selectively delegate tasks to AI rather than relinquishing control. This research showed that interfaces should respond to varying levels of user engagement and trust. Business Pivot: • Conduct thorough autonomy user research to uncover where automation adds value and where it can be disempowering. • Offer AI features that allow for cooperative user overrides and guidance, preserving a meaningful sense of agency. 2. AUTHENTIC RELATABILITY 'Humanizing' AI doesn't require crafting a digital clone. 'Human-like' AI captures headlines, but we've found that lifelike avatars, or agents that take on overly anthropomorphic qualities, can unsettle users. Instead, AI that focuses on clarity, transparency, and helpfulness fosters trust. In a study focused on AI companionship, we found that users consistently favored simple, utility-driven interactions over high-fidelity visual character designs. Abstract representations like voice or text were seen as more relatable than literal characters. We found that authentic, meaningful engagement stems more from tone and usefulness than from visual realism. • Resist the temptation for hyperrealism with agents. Instead, craft relatable interactions. • Use relationship design principles to shape AI interactions that feel authentic and empathetic, and build trust through utility, not appearance. 3. NATURAL IMMERSION Amid the buzz about cool new hardware devices and spatial computing, true immersion is often more about how experiences fit into everyday contexts. AI should naturally engage multiple senses—visual, auditory, and tactile—without requiring the latest trendy device. In our work with a leading consumer electronics brand, we prototyped several spatial computing concepts that enhanced desktop experiences without the need for headsets or external devices. Prototypes showed that by embedding 3D views and AI-driven interactions directly into familiar devices and workflows, we could create more intuitive and seamless forms of digital immersion. Business Pivot: • Invest in multi-modal AI interaction that engages sensory and spatial inputs to create more intuitive, natural experiences. • Integrate AI within existing products and ecosystems to amplify value at familiar touchpoints before pursuing entirely new solutions. 4. MEANINGFUL IMPACT The allure of fast AI deployment can overshadow a well-defined strategy. In the race to compete, many AI solutions have focused more on technological novelty than measurable substance. A lasting impact requires aligning AI initiatives with user needs to ensure solutions lead to quantifiable business outcomes. We observed development teams assuming AI would provide value at every stage in a user's workflow while working with a large consumer technology provider with a major AI platform. But this assumption resulted in an overloaded feature set with decreased adoption. By utilizing a human behavior value matrix, we helped developers identify a few signature moments that delivered higher, more measurable value. Also, by prototyping imagined scenarios, we were able to validate the viability of new AI within their software. Business Pivot: • Invest in proper research and design, focusing on long-term strategy and growth over short-term gains. • Prioritize use cases with meaningful ROI and user satisfaction over flashy features. Start small, prove value, and build on success. Within the AI hype cycle, where technological novelty can overshadow substance, there's an opportunity for companies to rise above the noise. The long-term potential for AI to shape industries and society is profound, yet we are in a stage where investments outweigh returns, and rapid experimentation is the norm. Now is the time for companies to step back and employ strategies that prioritize value. By embracing human-centered design principles of autonomy, relatability, immersion, and impact, companies can create AI experiences that transcend novelty and truly enhance human experiences while driving measurable ROI and business growth.
Forbes
3 days ago
- Business
- Forbes
The Year Of Agentic AI: Charting The Next Frontier For Intelligent Enterprises
Sateesh Seetharamiah, CEO of Edge Platforms, EdgeVerve Systems Limited. Today's business leaders face a pivotal moment. Organizations that have not yet embraced digital transformation and AI into their operations risk falling behind as the pace of innovation accelerates. AI integration is essential for operational excellence. And it must be more than simple rules-based chatbots; it is about using advanced large language models (LLMs) that are capable of synthesizing complex information. Recent industry insights reveal a rise in enterprise AI adoption. This trend will only intensify as organizations recognize the strategic value AI delivers across every business function. Now, enterprises are entering into the era of agentic AI, a transformative leap that redefines enterprise operations. Unlike traditional AI, agentic AI goes beyond passive analysis to deliver autonomous, intelligent action. These agents are digital executive partners. Agentic AI agents plan, adapt and execute sophisticated tasks in real time, unlocking new business models and driving productivity at scale. These agents anticipate needs, adapt to a shifting environment and support leaders in making timely, informed decisions. For instance, in the insurance world, agentic AI is streamlining claims processing. In the U.S., close to 62% of an insurer's expenses are related to claims. Insurance processors are often buried in data, trying to verify claims and work with customers. Rather than being the bottleneck, agentic AI streamlines this data review, cutting down the processing time and providing processors with the information needed and recommendations for next steps. This case is duplicated across multiple industries, from manufacturing to healthcare to transportation. Yet, the shift to agentic AI is not a simple incremental shift. Rather, it is a fundamental change in how work gets done across the enterprise. It empowers businesses to break down complex challenges into manageable actions without requiring constant human guidance and intervention. For example, in the banking sector, where analysts once spent hours evaluating loan requests, agentic AI can quickly assess market trends and applicant financials, recommend adjustments and accelerate decision cycles. The result is streamlined operations and enhanced business agility. Looking back to know how to move ahead To understand how enterprises got to this stage, we need to reflect on the journey of AI in the enterprise, beginning with when it was introduced to businesses in the 1980s. There is a clear evolution. Early AI implementations were rigid, rule-based systems that were effective for narrowly defined tasks but lacked the flexibility to adapt to dynamic business needs. As technology advanced, enterprises began leveraging AI for more sophisticated applications, including personalizing interactions and offering contextual analysis. Then the emergence of LLMs opened up new possibilities, enabling AI to interpret nuanced infrastructures and respond to diverse scenarios. While these models deliver significant value, their insights are inherently limited to the scope of the training data, underscoring the need for solutions that combine intelligence with real-time adaptability. Agentic AI answers this need. It fuses autonomous action with deep intelligence. The hybrid approach empowers enterprises to orchestrate real-time task execution with confidence. This marks a decisive step forward in enabling connected, intelligent operations that are both scalable and sustainable. Not surprisingly, agentic AI agents are expanding across enterprises, from customer service to product development, supply chain and more. A recent survey from BCG, found that 58% of companies are using AI agents while another 35% are exploring the adoption of agentic AI. This is not just a simple technology upgrade. It is a corporate, strategic priority, as it impacts business outcomes and competitiveness. Agentic AI empowers enterprise teams with real-time decision-making capabilities that unlock new values and innovations. As an extension of the human workforce, agentic AI unleashes greater productivity. Clarifying AI's role in the workforce While agentic AI offers greater intelligence and proactive operations, it is important to clarify its role in the workforce. The deployment of multiple agents for specific tasks amplifies efficiency, but it does not replace the human element. Rather, agentic AI liberates employees from repetitive, time-intensive responsibilities, allowing them to focus on strategic initiatives that drive business growth, profitability and enhance customer experience. Human oversight remains critical. Team members ensure that AI solutions are deployed responsibly, aligned with organizational policies and compliant with regulatory and ethical standards. Through active governance and real-time visibility, businesses can harness the full potential of agentic AI while safeguarding trust and accountability. The majority of employees want to use AI in their workflows. According to a recent McKinsey report, approximately 94% of employees are familiar with AI, with close to three times more employees using AI than leaders believe. While the knowledge base is there, enterprises are challenged with how to implement agentic AI in a manner that maximizes the benefits while minimizing risks related to biased outputs and security. A platform-based approach allows enterprises to manage and orchestrate multiple AI agents, ensuring efficient data use, control, governance and security. A scalable agentic AI platform provides a simple solution to what could have been a complex business initiative. Ultimately, agentic AI should be embraced as a strategic partner—one that extends the reach and impact of every team member. Enterprises that adopt a platform-first, integrated approach will unlock new levels of connectivity, intelligence and value creation. The future of business is being shaped by agentic AI through empowering organizations to lead with clarity, agility and purpose. Agentic AI is a transformative force reshaping every industry. Forbes Business Council is the foremost growth and networking organization for business owners and leaders. Do I qualify?
