Get Started<\/a><\/p>\n"}]},{"main_heading":"What is AI transformation?","content_block":[{"acf_fc_layout":"text","content":"AI transformation is a strategic initiative where businesses integrate artificial intelligence into their operations, products, and services to drive efficiency, innovation, and growth. Unlike general digital transformation, which focuses on adopting digital tools and processes, AI transformation specifically leverages machine learning, automation, and data-driven insights to create new business value.<\/p>\n
AI and digital transformation often work together: digital transformation lays the groundwork by digitizing processes and data, while AI transformation builds on this foundation to unlock advanced capabilities.<\/p>\n
Key components of AI transformation:<\/p>\n
\n- Process optimization:<\/strong> AI automates and enhances workflows, reducing manual effort and errors.<\/li>\n
- Data-driven decision making:<\/strong> AI enables better business insights by analyzing large volumes of data.<\/li>\n
- Customer experience enhancement:<\/strong> AI personalizes interactions, improving satisfaction and loyalty.<\/li>\n<\/ul>\n
According to Glide\u2019s The state of AI in operations 2025 report<\/span>, 73% of companies have already adopted AI<\/a> or are actively planning to. The question is no longer when to adopt AI, but how to scale it.<\/p>\nAI transformation vs. digital transformation: What\u2019s the difference?<\/h3>\n
AI is both a driver and a core component of digital transformation. Whereas digital transformation laid the foundation by moving operations to the cloud, connecting data sources, and automating workflows, AI transformation builds on this by creating a feedback loop. The data trains models, models drive action, and those actions generate new data to further refine performance.<\/p>\n
This shift marks a new phase in enterprise evolution. Instead of simply digitizing workflows, organizations are now designing intelligent systems that respond to change and deliver higher-impact outcomes.<\/p>\n
\n
\n\n\n\t| Focus area<\/th> | Digital transformation<\/th> | AI transformation<\/th>\n<\/tr>\n<\/thead>\n |
\n\n\t| Customer experience<\/td> | CRM platforms, self-service portals<\/td> | AI-powered support, personalized messaging<\/td>\n<\/tr>\n |
\n\t| Operations<\/td> | Process automation, task tracking<\/td> | Predictive workflows, auto-routing, outcome optimization<\/td>\n<\/tr>\n |
\n\t| Data usage<\/td> | Dashboards, scheduled reports<\/td> | Real-time analysis, next-step recommendations<\/td>\n<\/tr>\n |
\n\t| Product innovation<\/td> | Centralized tools for product teams<\/td> | Generative tools for ideation and testing<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/p>\n Once businesses integrate AI into their systems, the impact is clear: 52% report a transformational impact on operations<\/span><\/a>, compared to 28% who expected that outcome. AI drives change across more areas, with more speed and visibility.<\/p>\n"},{"acf_fc_layout":"colored_notification","text":"Discover how to automate smarter, work faster, and make better decisions using monday AI Blocks, with a short lesson in monday academy. <\/span>Learn how to use monday\u2019s AI Blocks.<\/span><\/a><\/p>\n","quote":false,"author":"","position":"","avatar":false}]},{"main_heading":"Key AI technologies driving enterprise innovation","content_block":[{"acf_fc_layout":"text","content":"Organizations are moving past experimentation and building AI directly into how work happens. The result is faster execution, fewer manual tasks, and better decisions.<\/p>\n Google\u2019s ROI of Gen AI report found that 45% of companies seeing productivity gains say generative AI has doubled employee output<\/span><\/a>. This isn\u2019t a marginal lift. It\u2019s a complete shift in how teams produce, plan, and deliver work.<\/p>\nHere are 4 core technologies driving that shift:<\/p>\n \n \n\n\n\t| Technology<\/th> | What it does<\/th> | Use case<\/th> | Real-world example<\/th>\n<\/tr>\n<\/thead>\n | \n\n\t| Machine learning<\/td> | Finds patterns in large data sets<\/td> | Forecasting, trend detection<\/td> | Predicting pipeline risk with sales ops models <\/td>\n<\/tr>\n | \n\t| Natural language processing (NLP)<\/td> | Understands and generates human language<\/td> | Ticket triage, content summarization<\/td> | Auto-tagging and routing customer requests<\/td>\n<\/tr>\n | \n\t| Computer vision<\/td> | Interprets visual information<\/td> | Quality checks, inventory tracking<\/td> | Flagging product defects in packaging<\/td>\n<\/tr>\n | \n\t| Generative AI<\/td> | Produces new content from prompts or data<\/td> | Copywriting, idea generation<\/td> | Creating blog outlines from support transcripts<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/p>\n When deployed through low-code or no-code tools, these technologies scale faster and deliver higher returns. In fact, 59% of companies say AI built on no or low-code platforms delivers the most transformational impact<\/span><\/a>.<\/p>\nThat\u2019s why AI integration<\/span><\/a> matters. AI tools work best when they\u2019re accessible, easy to adopt, and tied directly into how teams already get work done.<\/p>\nWhat agentic AI means for enterprises<\/h3>\nBeyond individual tools, a new class of AI that can act autonomously is emerging. This is known as agentic AI and refers to autonomous systems that make decisions and execute tasks with minimal input. These tools don\u2019t just assist \u2014 they act. They initiate systems, adapt to context, and evolve based on new information.<\/p>\n This isn\u2019t a futuristic concept, though, with 47% of AI adopters already use agentic tools<\/span><\/a>. Over half already report a transformational impact from automating tasks like data processing and support ticket handling.<\/p>\nHere\u2019s what an agentic workflow could look like:<\/p>\n | |