With continued uncertainty in the market about global economic conditions and the pressure to control supply-chain costs, there\u2019s more need than ever in 2025 for newer, smarter operational strategies. As we edge further into this year, it\u2019s important for businesses to consider how they can continue to drive greater efficiencies and lower costs, while still evolving to modernise their tech stack and prepare the business to pursue new opportunities for growth. <\/p>\n\n\n\n
As AI continues to redefine how businesses compete and operate, Agentic AI has emerged as an especially promising solution for a more intelligent and self-sufficient way of working. In a shift from assisted intelligence to genuine autonomy, industry experts anticipate accelerating interest in agentic AI investment, predicting enterprise adoption to spike to 33% by 2028<\/a> \u2014 an exponential leap from less than 1% in 2024. <\/p>\n\n\n\n Yet it\u2019s not only about Agents, and realising the desired outcomes from AI requires a slightly broader strategic perspective. With the right blend of AI patterns and an accessible, intuitive no-code platform, these intelligent AI-powered tools can empower organisations to unlock unprecedented levels of productivity, fostering a collaborative ecosystem where human and digital talent work in sync to drive innovation. <\/p>\n\n\n\n While AI provides an extremely broad spectrum of transformative capability, it can be distilled down into three essential patterns – generative, predictive, and agentic AI \u2013 which each serve distinct purposes. Gen AI takes patterns learned from vast datasets<\/a> and uses them to generate novel content \u2014 from text and images to music and code. Predictive AI, on the other hand, analyses historical data to forecast future outcomes, providing crucial insights for informed decision-making across various business functions. Unlike the former two, which are largely passive in their operation, agentic AI is capable of thinking and acting autonomously based on learned behaviours. It can perform complex tasks, automate workflows, and adapt to changing conditions with minimal human intervention.<\/p>\n\n\n\n As one of the latest developments in artificial intelligence, agentic AI operates with a high degree of autonomy, while maintaining real-time adaptability and human oversight. It analyses data, understands contexts, and executes complex actions within pre-defined parameters. Powered by machine learning, large language models (LLMs), and reasoning engines, it continuously applies and acts upon its intelligence while working alongside human employees.<\/p>\n\n\n\n The powerful capabilities of Agents can immediately create concerns about loss of jobs; this theme dominates many news cycles these days. However, we believe this actually creates an opportunity for most information workers to create new value and allow job expansion. For the individual, Agentic AI reduces the time spent on routine activities, such as data entry, synchronising information across systems, or completing highly repetitive tasks. This creates space for employees to focus on more strategic, creative and high-priority tasks. This shift doesn\u2019t replace human roles\u2014it co-exists with them, ensuring people work in harmony with AI for greater efficiency, creativity, and decision-making.<\/p>\n\n\n\n Furthermore, the use of new AI agents is rapidly requiring the building of many new skills and talents. In terms of job creation, this shift is already taking place across various industries. According to a 2025 Job Market Research report, AI-related job postings peaked at 16,000 in October 2024<\/a>, showing rapid growth in newly established roles. AI\u2019s integration into day-to-day operational processes necessitates new roles in developing, deploying, and managing these intelligent systems. <\/p>\n\n\n\n This need for rare human talent subsequently creates knowledge gaps for companies fighting to maintain competitiveness in the tech \u2018space race\u2019. As a result, the demand for tools that make AI initiatives more accessible for a broader range of employees has soared. Businesses who empower employees at all levels to work alongside AI create a more agile, adaptable, and collaborative workforce.<\/p>\n\n\n\n Insiders predict that Agentic AI will be one of the biggest strategic trends over the next few years. Gartner predicts that by 2028, one-third of interactions with GenAI will invoke autonomous agents to complete tasks. Across every industry, businesses are beginning to apply Agents to optimise processes, improve productivity, and unlock new revenue streams. With the power to \u2018learn on the job\u2019 and gradually improve over time, agentic AI is particularly well-suited for supporting staff in stakeholder interactions.\u00a0<\/p>\n\n\n\n Timing is everything \u2014 especially when it comes to effectively managing the workforce. While basic AI-powered chatbots allowed companies to shift customer services from limited hours to 24\/7 support<\/a>, agentic AI takes this a step further, making interactions more dynamic and context-aware.\u00a0<\/p>\n\n\n\n Retailers, for instance, can use agentic AI to answer customer queries, process refunds, or make product recommendations, reducing the need for human agents to handle routine tasks. Unlike traditional automation, these AI-driven agents learn from each interaction, improving their responses over time. When escalations do occur, agentic AI analyses them to refine its approach and ensure human agents receive the most relevant context before stepping in. <\/p>\n\n\n\n This human-digital collaboration is where the true potential of AI lies. Rather than replacing jobs, agentic AI enables employees to focus on solving complex customer issues, fostering stronger relationships, and delivering a superior experience.<\/p>\n\n\n\n Agentic AI is becoming a prevalent tool for business transformation. But with the growing concerns regarding the scarcity of tech talent, organisations are left wondering where to begin implementing agentic AI. <\/p>\n\n\n\n To address this problem, experts predict<\/a> a drastic increase in demand for citizen platforms that provide simpler tools and which unify diverse AI stacks and seamlessly orchestrate machine learning, generative AI, and agentic automation. As such, no-code platforms are emerging as an important solution, rapidly gaining popularity due<\/a> to the shortage of developer skills.<\/p>\n\n\n\n Taking a less technical approach to software development, no-code platforms can be the ideal entry point for agentic AI implementation and deployment. These platforms enable employees to build applications with no programming skills required. This allows for the easy customisation of intelligent agents and support portals, while eliminating the daunting complexity of traditional coding \u2014 saving both time and money, and bridging knowledge gaps. <\/p>\n\n\n\n As we progress into 2025, it\u2019s up to organisations to find ways to implement this technology beneficial for both the workforce and the bottom line. It all boils down to strategic planning, resourceful upskilling, and responsible AI agent implementation. The future of work is AI-augmented, not AI-replaced. The key to success lies in human and digital talent working together, empowering businesses to scale AI innovation while at the same time realising operational efficiencies.<\/p>\n","protected":false},"excerpt":{"rendered":" Burley Kawasaki, Global VP of Product Marketing and Strategy at Creatio, evaluates the potential of \u201cagentic\u201d AI. <\/p>\n","protected":false},"author":480,"featured_media":22953,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"apple_news_api_created_at":"","apple_news_api_id":"","apple_news_api_modified_at":"","apple_news_api_revision":"","apple_news_api_share_url":"","apple_news_cover_media_provider":"image","apple_news_coverimage":0,"apple_news_coverimage_caption":"","apple_news_cover_video_id":0,"apple_news_cover_video_url":"","apple_news_cover_embedwebvideo_url":"","apple_news_is_hidden":"","apple_news_is_paid":"","apple_news_is_preview":"","apple_news_is_sponsored":"","apple_news_maturity_rating":"","apple_news_metadata":"\"\"","apple_news_pullquote":"","apple_news_pullquote_position":"","apple_news_slug":"","apple_news_sections":[],"apple_news_suppress_video_url":false,"apple_news_use_image_component":false,"footnotes":""},"categories":[3],"tags":[],"topic":[614],"class_list":["post-22952","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-the-interface","topic-data-ai"],"acf":[],"apple_news_notices":[],"yoast_head":"\nBreaking down the AI triad: Generative, predictive, and agentic <\/h3>\n\n\n\n
Agentic AI and the workforce<\/h3>\n\n\n\n
Agentic AI on the front line <\/h3>\n\n\n\n
Getting started with no-code AI building<\/h3>\n\n\n\n