{"id":7984,"date":"2026-01-29T19:09:46","date_gmt":"2026-01-29T13:39:46","guid":{"rendered":"https:\/\/codewave.com\/insights\/?p=7984"},"modified":"2026-01-29T19:09:48","modified_gmt":"2026-01-29T13:39:48","slug":"understanding-ai-vs-generative-ai-differences","status":"publish","type":"post","link":"https:\/\/codewave.com\/insights\/understanding-ai-vs-generative-ai-differences\/","title":{"rendered":"Understanding AI vs. Generative AI for Enterprises"},"content":{"rendered":"\n<p>Artificial Intelligence (AI) and Generative AI may seem similar at first glance, but enterprises experience their effects very differently. Traditional AI systems are primarily used to analyze data, automate routine processes, and support decision\u2011making, for example, predicting customer churn, automating supply\u2011chain alerts, or detecting anomalies in transaction logs. These applications help organizations become more efficient and reduce manual workload.<\/p>\n\n\n\n<p>Generative AI, on the other hand, is designed to produce new content and outputs such as code suggestions, product descriptions, marketing copy, or synthetic data for simulations.<\/p>\n\n\n\n<p>This blog will explore the key differences between AI and Generative AI, their impact on business operations, and how enterprises can use each to drive growth and innovation.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"7d00d524-c7af-4b57-ba67-e604107f5828\"><span id=\"key-takeaways\"><strong>Key Takeaways<\/strong><\/span><\/h2>\n\n\n\n<ul>\n<li><strong>AI and Generative AI differ<\/strong>: Traditional AI focuses on data analysis, prediction, and automation, while generative AI excels at creating new content like text, images, and videos.<\/li>\n\n\n\n<li><strong>AI solves operational challenges<\/strong>: It enhances decision-making, automates workflows, and optimizes processes in areas like forecasting and resource allocation.<\/li>\n\n\n\n<li><strong>Generative AI drives creativity<\/strong>: It supports content creation at scale, personalises customer experiences, and assists with design, but it requires domain-specific training to be effective.<\/li>\n\n\n\n<li><strong>Integration is key<\/strong>: Successful AI and generative AI projects depend on strong data governance, seamless integration with business processes, and clear ROI goals.<\/li>\n\n\n\n<li><strong>AI and Generative AI can coexist<\/strong>: AI handles analytics and prediction, while generative AI adds creativity and personalisation to business applications.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"48703b22-a29d-456b-8b18-d2d8bb456fa9\"><span id=\"what-is-artificial-intelligence-and-how-is-it-used-in-business\"><strong>What Is Artificial Intelligence and How Is It Used in Business?<\/strong><\/span><\/h2>\n\n\n\n<p><a target=\"_blank\" rel=\"noreferrer noopener\" href=\"https:\/\/codewave.com\/insights\/advanced-ai-solutions-enterprises-guide\/\"><strong><u>Artificial Intelligence<\/u><\/strong><\/a> refers to computational systems that perform tasks historically requiring human intelligence. These tasks include pattern recognition, prediction, optimisation, and decision support.&nbsp;<\/p>\n\n\n\n<p>At the enterprise level, traditional AI broadly encompasses machine learning, <a target=\"_blank\" rel=\"noreferrer noopener\" href=\"https:\/\/codewave.com\/insights\/data-analytics-strategy-effective-creation\/\"><strong><u>data analytics,<\/u><\/strong><\/a> expert systems, and automation models.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"1ae24884-3807-4a00-9693-9c84b1ee9af9\"><span id=\"the-core-idea-behind-ai\"><strong>The Core Idea Behind AI<\/strong><\/span><\/h3>\n\n\n\n<p>AI systems operate through algorithms that learn patterns from data. Once trained, these systems can:<\/p>\n\n\n\n<ul>\n<li>Predict outcomes (e.g., forecast demand or churn).<\/li>\n\n\n\n<li>Classify information (e.g., segment customers).<\/li>\n\n\n\n<li>Automate repetitive workflows.<\/li>\n\n\n\n<li>Support decisions with data\u2011driven recommendations.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"554eb309-920d-4330-b5ec-2420717d6b1d\"><span id=\"types-of-ai-relevant-to-enterprises\"><strong>Types of AI Relevant to Enterprises<\/strong><\/span><\/h3>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td><strong>Category<\/strong><\/td><td><strong>Description<\/strong><\/td><td><strong>Typical Use Cases<\/strong><\/td><\/tr><tr><td><strong>Rule\u2011based Systems<\/strong><\/td><td>Follow explicit instructions and business rules<\/td><td>Workflow automation, alert triggers<\/td><\/tr><tr><td><strong>Machine Learning (ML)<\/strong><\/td><td>Learns patterns from labelled data<\/td><td>Demand forecasting, fraud detection<\/td><\/tr><tr><td><strong>Neural Networks \/ Deep Learning<\/strong><\/td><td>Learns complex patterns from large datasets<\/td><td>Image or voice recognition<\/td><\/tr><tr><td><strong>Predictive Models<\/strong><\/td><td>Estimates future outcomes based on historical patterns<\/td><td>Sales forecasting, customer lifetime value<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"d5aba464-f605-4381-99c3-9d7ceba9254c\"><span id=\"how-enterprises-apply-ai\"><strong>How Enterprises Apply AI<\/strong><\/span><\/h3>\n\n\n\n<p>Traditional AI strengths are best realised where structured data exists, and clear objectives can be defined. Common enterprise applications include:<\/p>\n\n\n\n<ul>\n<li><strong>Customer analytics:<\/strong> Segmenting audiences and predicting behaviour.<\/li>\n\n\n\n<li><strong>Operations:<\/strong> Optimising supply chains and automating back\u2011office tasks.<\/li>\n\n\n\n<li><strong>Sales and marketing:<\/strong> Scoring leads and recommending next best actions.<\/li>\n\n\n\n<li><strong>Risk management:<\/strong> Detecting anomalies or assessing compliance.<\/li>\n<\/ul>\n\n\n\n<p>The largest segments of traditional enterprise AI markets today include predictive analytics, process automation, and intelligent data processing.&nbsp;<\/p>\n\n\n\n<p><strong>Also Read: <\/strong><a target=\"_blank\" rel=\"noreferrer noopener\" href=\"https:\/\/codewave.com\/insights\/generative-ai-software-testing-automation\/\"><strong><u>10 Ways Generative AI Will Enhance Software Testing<\/u><\/strong><\/a><\/p>\n\n\n\n<p><em>Transform your workflows with smart automation tools that improve efficiency and save time. <\/em><a target=\"_blank\" rel=\"noreferrer noopener\" href=\"https:\/\/codewave.com\/service\/gen-ai-development\/\"><strong><em><u>Codewave\u2019s GenAI Development<\/u><\/em><\/strong><\/a><em> integrates seamlessly into your processes, from 24\/7 customer engagement to automated report generation, helping you work smarter, not harder.<\/em><\/p>\n\n\n\n<p>While AI focuses on prediction and automation, generative AI takes a fundamentally different approach. Let&#8217;s take a closer look at how this technology redefines creativity<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"aa9a8f27-7fe1-46e4-8fe0-865c93029689\"><span id=\"what-is-generative-ai-and-how-does-it-differ-from-traditional-ai\"><strong>What Is Generative AI and How Does It Differ from Traditional AI?<\/strong><\/span><\/h2>\n\n\n\n<p>Generative AI is a subclass of artificial intelligence focused on producing new content. Unlike <a target=\"_blank\" rel=\"noreferrer noopener\" href=\"https:\/\/codewave.com\/insights\/predictive-analytics-tools\/\"><strong><u>predictive models<\/u><\/strong><\/a> that forecast outcomes, generative systems synthesise new output such as text, code, imagery, or entire workflows based on learned patterns.<\/p>\n\n\n\n<p>At the core of generative AI are large models, such as transformers, that use unsupervised and self\u2011supervised learning to understand language, structure, and relationships in data.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"f816caca-2210-4842-9ac6-3ab6135cc41c\"><span id=\"generative-ai-defined\"><strong>Generative AI Defined<\/strong><\/span><\/h3>\n\n\n\n<p>Generative AI:<\/p>\n\n\n\n<ul>\n<li><strong>Creates new content<\/strong> (text, images, audio, code).<\/li>\n\n\n\n<li><strong>Uses large pretrained models<\/strong> trained on massive datasets.<\/li>\n\n\n\n<li>Can follow prompts to produce outputs that mimic human creativity.<\/li>\n<\/ul>\n\n\n\n<p>Examples include models that write articles, generate code snippets, craft customer email responses, translate between formats, or design visuals.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"60e5fb80-e964-466c-88be-503f037e80e6\"><span id=\"generative-ai-vs-traditional-ai\"><strong>Generative AI vs Traditional AI<\/strong><\/span><\/h3>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td><strong>Feature<\/strong><\/td><td><strong>Traditional AI<\/strong><\/td><td><strong>Generative AI<\/strong><\/td><\/tr><tr><td><strong>Primary Focus<\/strong><\/td><td>Prediction, classification, optimisation<\/td><td>Content creation and simulation<\/td><\/tr><tr><td><strong>Input Requirements<\/strong><\/td><td>Structured or labelled datasets<\/td><td>Large corpus of raw data<\/td><\/tr><tr><td><strong>Output<\/strong><\/td><td>Scores, categories, forecasts<\/td><td>New text, images, audio, code<\/td><\/tr><tr><td><strong>Typical Models<\/strong><\/td><td>Decision trees, regression, shallow ML<\/td><td>Large language models (LLMs), GANs<\/td><\/tr><tr><td><strong>Use Cases<\/strong><\/td><td>Forecasting, automation<\/td><td>Creative tasks, summarisation, generative design<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>Generative AI\u2019s ability to synthesise novel outputs distinguishes it from other AI forms. Traditional AI excels at making sense of data; generative AI can produce entirely new material that didn\u2019t exist before.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"0bd31775-1f08-4e38-9b35-93892ed046dd\"><span id=\"market-growth-trends\"><strong>Market Growth Trends<\/strong><\/span><\/h3>\n\n\n\n<p>Generative AI is expanding faster than traditional AI segments. Projections vary, but the generative AI market is expected to grow by more than <a target=\"_blank\" rel=\"noreferrer noopener\" href=\"https:\/\/www.azilen.com\/blog\/generative-ai-statistics\/\"><strong><u>30% annually in the near <\/u><\/strong><\/a>term, and some forecasts project growth well beyond that by the end of the decade.&nbsp;<\/p>\n\n\n\n<p><strong>Also Read: <\/strong><a target=\"_blank\" rel=\"noreferrer noopener\" href=\"https:\/\/codewave.com\/insights\/stages-ai-development\/\"><strong><u>What&#8217;s Next for AI? The Stages of Development You Need to Know in 2026<\/u><\/strong><\/a><\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"6502a672-b071-420e-949e-64f1ba46b953\"><span id=\"what-business-problems-can-ai-solve-and-where-does-generative-ai-fit\"><strong>What Business Problems Can AI Solve, and Where Does Generative AI Fit?<\/strong><\/span><\/h2>\n\n\n\n<p>AI and Generative AI address distinct challenges within organizations. Understanding these differences is crucial for businesses to allocate resources wisely and achieve targeted outcomes.&nbsp;<\/p>\n\n\n\n<p>Both technologies can coexist to address complementary needs, driving efficiencies and fostering innovation.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"5d4e3989-1741-4bea-ab98-f7cd1bfe65c2\"><span id=\"traditional-ai-solves-these-enterprise-needs\"><strong>Traditional AI Solves These Enterprise Needs<\/strong><\/span><\/h3>\n\n\n\n<p><strong>1. Process Optimisation<\/strong><\/p>\n\n\n\n<p>AI is particularly effective at <strong>optimizing business processes<\/strong> by analyzing data and automating workflows. Traditional AI uses algorithms to streamline operations, reducing cycle times and optimising resource allocation.<\/p>\n\n\n\n<ul>\n<li><strong>Reducing cycle times<\/strong>: AI identifies process bottlenecks and automates repetitive tasks, accelerating workflows and shortening time-to-market.<\/li>\n\n\n\n<li><strong>Enhancing resource allocation<\/strong>: Predictive models use historical data to forecast demand, enabling more efficient deployment of people and resources.<\/li>\n<\/ul>\n\n\n\n<p><strong>2. Predictive Decision Suppor<\/strong>t<\/p>\n\n\n\n<p>AI excels at predictive analytics, which uses historical and real-time data to forecast future outcomes. This enables businesses to make proactive, data-driven decisions.<\/p>\n\n\n\n<ul>\n<li><strong>Forecasting sales or revenues<\/strong>: Machine learning models predict future sales based on customer behaviour patterns and historical sales data.<\/li>\n\n\n\n<li><strong>Predicting supply chain disruptions<\/strong>: AI models analyse data from suppliers, logistics, and production systems to forecast disruptions and suggest alternative plans.<\/li>\n<\/ul>\n\n\n\n<p><strong>3. Automation of Repetitive Tasks<\/strong><\/p>\n\n\n\n<p>AI thrives in automating repetitive tasks, enabling employees to focus on higher-value activities. With intelligent workflow management, businesses can significantly reduce manual errors and improve operational efficiency.<\/p>\n\n\n\n<ul>\n<li><strong>Intelligent workflow management<\/strong>: AI-driven automation tools route tasks to the right employees, prioritize based on urgency, and track progress in real time.<\/li>\n\n\n\n<li><strong>Data cleansing and integration<\/strong>: AI tools automatically detect and clean inconsistencies in large datasets, ensuring data integrity and seamless integration across platforms.<\/li>\n<\/ul>\n\n\n\n<p><strong>4. Knowledge Extraction<\/strong><\/p>\n\n\n\n<p>AI models help extract actionable insights from massive datasets that would otherwise be too complex to analyse manually.<\/p>\n\n\n\n<ul>\n<li><strong>Identifying patterns in large datasets: <\/strong>AI algorithms mine data for trends, enabling businesses to uncover valuable insights into customer preferences, market dynamics, and operational inefficiencies.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"6d529f34-8212-4535-aacd-312c9113342a\"><span id=\"generative-ai-solves-different-problems\"><strong>Generative AI Solves Different Problems<\/strong><\/span><\/h3>\n\n\n\n<p>Generative AI, on the other hand, excels when the task requires generating new content or creative output, rather than analysis or optimization. It focuses on creativity, customization, and personalization.<\/p>\n\n\n\n<p><strong>1. Content Generation at Scale<\/strong><\/p>\n\n\n\n<p>Generative AI can rapidly produce high-quality, scalable content for a wide range of business needs.<\/p>\n\n\n\n<ul>\n<li><strong>Generate product descriptions<\/strong>: Using natural language processing (NLP) and large language models, Generative AI can write product descriptions, blog posts, and marketing copy at scale.<\/li>\n\n\n\n<li><strong>Generate reports or support responses<\/strong>: By drawing from existing data, Generative AI can create comprehensive reports or automated responses for customer service.<\/li>\n<\/ul>\n\n\n\n<p><strong>2. Personalization Engines<\/strong><\/p>\n\n\n\n<p>Generative AI enables businesses to offer <strong>highly personalized user experiences<\/strong> by tailoring content and interactions in real time.<\/p>\n\n\n\n<ul>\n<li><strong>Provide tailored messaging<\/strong>: Generative models use customer data and preferences to craft personalised marketing messages, increasing engagement and conversion rates.<\/li>\n\n\n\n<li><strong>Custom user experiences<\/strong>: Whether through dynamic website content or personalised email campaigns, Generative AI customises the user journey based on real-time interactions and preferences.<\/li>\n<\/ul>\n\n\n\n<p><strong>3. Assistance for Knowledge Workers<\/strong><\/p>\n\n\n\n<p>Generative AI can assist knowledge workers by <strong>automating content-heavy tasks<\/strong> such as drafting proposals, summarising documents, or personalising communication.<\/p>\n\n\n\n<ul>\n<li><strong>Draft proposals<\/strong>: Generative models assist in writing proposals by synthesising relevant data and producing drafts based on specified parameters.<\/li>\n\n\n\n<li><strong>Summarise documents<\/strong>: AI tools quickly process and summarise lengthy reports, contracts, or research papers, saving employees significant time.<\/li>\n<\/ul>\n\n\n\n<p><strong>4. Creative Design Support<\/strong><\/p>\n\n\n\n<p>Generative AI plays a pivotal role in <strong>creative tasks<\/strong>, including design, prototyping, and visual asset generation.<\/p>\n\n\n\n<ul>\n<li><strong>Generate visual assets<\/strong>: Tools such as DALL\u00b7E and DeepArt use AI to generate logos, graphics, and illustrations from text prompts, helping designers create high-quality visuals quickly.<\/li>\n\n\n\n<li><strong>Prototype interfaces<\/strong>: Generative AI can generate initial design prototypes, accelerating the design phase and enhancing collaboration between design teams and stakeholders.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"c430a4a2-5651-4893-8323-fe617d070d0c\"><span id=\"comparative-use-cases-ai-vs-generative-ai\"><strong>Comparative Use Cases: AI vs Generative AI<\/strong><\/span><\/h3>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td><strong>Use Case Category<\/strong><\/td><td><strong>Traditional AI<\/strong><\/td><td><strong>Generative AI<\/strong><\/td><\/tr><tr><td><strong>Forecasting demand from data<\/strong><\/td><td>Strong<\/td><td>Limited<\/td><\/tr><tr><td><strong>Creating marketing copy<\/strong><\/td><td>Possible (templates)<\/td><td>Primary<\/td><\/tr><tr><td><strong>Summarising large documents<\/strong><\/td><td>Possible with NLP<\/td><td>High accuracy and context<\/td><\/tr><tr><td><strong>Automating workflows<\/strong><\/td><td>Strong<\/td><td>Complementary<\/td><\/tr><tr><td><strong>Generating code<\/strong><\/td><td>Emerging<\/td><td>High productivity gains<\/td><\/tr><tr><td><strong>Synthesizing images<\/strong><\/td><td>Not applicable<\/td><td>Primary<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p><strong>Also Read: <\/strong><a target=\"_blank\" rel=\"noreferrer noopener\" href=\"https:\/\/codewave.com\/insights\/understanding-multi-modal-ai-technology\/\"><strong><u>Why Multi-Modal AI is the Next Big Thing in Artificial Intelligence<\/u><\/strong><\/a><\/p>\n\n\n\n<p><em>Free your team from mundane tasks and scale your business with AI-powered tools like predictive analytics and conversational bots. <\/em><a target=\"_blank\" rel=\"noreferrer noopener\" href=\"https:\/\/codewave.com\/service\/ai-and-machine-learning-development-company\/\"><strong><em><u>Codewave\u2019s AI\/ML Development<\/u><\/em><\/strong><\/a><em>delivers custom solutions that improve decision-making, automate operations, and enhance customer experiences.<\/em><\/p>\n\n\n\n<p>However, like all technologies, AI and generative AI present their own challenges. Let\u2019s examine some of the most common limitations and how to overcome them<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"3110515e-3598-48d9-9835-094f8f9a8242\"><span id=\"common-limitations-and-risks-in-ai-and-generative-ai-projects-for-enterprises\"><strong>Common Limitations and Risks in AI and Generative AI Projects for Enterprises<\/strong><\/span><\/h2>\n\n\n\n<p>AI and generative AI hold clear potential, but realising that potential requires disciplined execution.&nbsp;<\/p>\n\n\n\n<p>A growing body of evidence shows that most enterprise AI efforts fail to deliver measurable impact when fundamental governance, integration, and data requirements are not met.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"b6cac441-9351-43ea-a36a-8334301805b5\"><span id=\"integration-and-roi-shortfalls\"><strong>Integration and ROI Shortfalls<\/strong><\/span><\/h3>\n\n\n\n<p>AI and generative AI investments often stall not because the technology is ineffective, but because they are not embedded into core business processes.<\/p>\n\n\n\n<ul>\n<li>Many pilots operate as isolated experiments rather than enterprise\u2011wide solutions, leaving integration gaps between AI outputs and operational workflows.<\/li>\n\n\n\n<li>Only a minority of organizations treat AI performance metrics as part of strategic KPIs such as revenue growth, cost savings, speed of delivery, or customer retention, weakening accountability for measurable returns.<\/li>\n\n\n\n<li>Failure to specify success criteria before implementation makes performance measurement arbitrary and ROI elusive.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"63e24bbc-8256-4886-8622-6d3027a74203\"><span id=\"data-quality-and-governance-failures\"><strong>Data Quality and Governance Failures<\/strong><\/span><\/h3>\n\n\n\n<p>High\u2011quality, well\u2011governed data is non\u2011negotiable for AI success. Yet survey data shows <a target=\"_blank\" rel=\"noreferrer noopener\" href=\"https:\/\/www.qlik.com\/us\/news\/company\/press-room\/press-releases\/data-quality-is-not-being-prioritized-on-ai-projects\"><strong><u>nearly 80% of organizations struggle<\/u><\/strong><\/a>with data quality issues that put AI ROI at risk.<\/p>\n\n\n\n<ul>\n<li>Fragmented data across business units results in inconsistent inputs for model training and decision support.<\/li>\n\n\n\n<li>Poor data governance leads to models trained on outdated or biased datasets, which in turn output inaccurate predictions or irrelevant generative content.<\/li>\n\n\n\n<li>Incomplete lineage and the lack of provenance tracking mean that organizations cannot explain or justify model decisions, thereby eroding trust in AI results.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"9c2a0326-0ec2-4c60-b264-c0fe14398c66\"><span id=\"security-and-privacy-exposure\"><strong>Security and Privacy Exposure<\/strong><\/span><\/h3>\n\n\n\n<p>Business use of generative AI tools often expands rapidly without adequate security controls, creating significant exposure.<\/p>\n\n\n\n<ul>\n<li>Unmanaged or \u201cshadow AI\u201d use by employees accessing AI tools through personal accounts frequently bypasses security policies, increasing risk exposure.<\/li>\n\n\n\n<li>Large language models and generative systems can amplify existing vulnerabilities, such as prompt injection or data leakage, if governance frameworks do not enforce access control and output review.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"aa68572e-bf7e-47de-bddb-89bd4f65ec6a\"><span id=\"bias-compliance-and-ethical-challenges\"><strong>Bias, Compliance, and Ethical Challenges<\/strong><\/span><\/h3>\n\n\n\n<p>AI systems mirror the data they are trained on. Without deliberate bias control and model transparency, outputs can reinforce unfair outcomes or violate regulatory requirements:<\/p>\n\n\n\n<ul>\n<li>Nearly half of organizations cite <strong>data bias and accuracy concerns<\/strong> as top challenges to adoption, which directly affect ethical compliance and trust in AI outputs.<\/li>\n\n\n\n<li>Compliance frameworks, such as NIST\u2019s AI Risk Management Framework, recommend governance at every life\u2011cycle stage to manage risks related to privacy, fairness, and legal accountability.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"d318be09-c1d4-4d16-9cf3-78b4a393971a\"><span id=\"skill-gaps-and-change-adoption-barriers\"><strong>Skill Gaps and Change Adoption Barriers<\/strong><\/span><\/h3>\n\n\n\n<p>Technical expertise remains scarce across enterprises, and a lack of trained personnel slows adoption, reduces effectiveness, and increases maintenance costs:<\/p>\n\n\n\n<ul>\n<li>A significant share of businesses report insufficient generative AI expertise as a critical barrier, which correlates with stalled projects and low ROI.<\/li>\n\n\n\n<li>Change resistance within teams and the absence of structured training programs limit user adoption and reduce the usefulness of deployed models.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"9af90785-eec7-4061-b6b9-95cb1a0b6cbe\"><span id=\"actionable-steps-for-enterprise-leaders\"><strong>Actionable Steps for Enterprise Leaders<\/strong><\/span><\/h2>\n\n\n\n<p>To move AI and generative AI projects beyond pilot phases and into scalable, measurable success, business leaders must implement the following strategies:<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"6dcb79f1-1230-4b79-9ddf-0e88788fdd94\"><span id=\"1-assign-clear-business-targets-before-deployment\"><strong>1. Assign Clear Business Targets Before Deployment<\/strong><\/span><\/h3>\n\n\n\n<p>Link AI initiatives directly to concrete business outcomes, such as cost reduction, revenue growth, or efficiency improvements. Avoid abstract goals and focus on quantifiable metrics like time saved, revenue uplift, or operational cost reductions.&nbsp;<\/p>\n\n\n\n<p>For instance, set a target like &#8220;<strong>Reduce customer service response time by 30% within 6 months<\/strong>&#8221; to ensure measurable results.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"f9b36246-43d1-45b5-bcba-425031935ebe\"><span id=\"2-build-data-foundations-first\"><strong>2. Build Data Foundations First<\/strong><\/span><\/h3>\n\n\n\n<p>AI and generative AI models rely on high-quality, well-integrated data. Organisations must prioritise data governance and data validation frameworks before deploying any models. Data pipelines and quality checks are essential for effective AI model training and business alignment.&nbsp;<\/p>\n\n\n\n<p>Tools such as Apache Kafka for real-time data integration and Snowflake for cloud data storage can help ensure data consistency.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"62a629f0-83e1-4386-b53b-62b8c90d45c4\"><span id=\"3-select-tools-that-support-fine%e2%80%91tuning-and-contextualization\"><strong>3. Select Tools That Support Fine\u2011Tuning and Contextualization<\/strong><\/span><\/h3>\n\n\n\n<p>Generic AI models often fail to meet the specific needs of an organization. Select custom solutions, such as those from <a target=\"_blank\" rel=\"noreferrer noopener\" href=\"https:\/\/codewave.com\/\"><strong><u>Codewave<\/u><\/strong><\/a> or other platforms that support customization, domain-specific training, and seamless integration with existing business systems.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"ab233d6f-a362-4614-9f8f-1faa7f24eb4e\"><span id=\"4-integrate-ai-across-business-workflows\"><strong>\u200b\u200b4. Integrate AI Across Business Workflows<\/strong><\/span><\/h3>\n\n\n\n<p>Instead of deploying AI as a standalone tool, integrate it directly into existing business processes, such as supply chain optimisation, sales forecasting, or financial analytics. Embedding AI into workflows ensures automated actions are based on real-time data and insights.&nbsp;<\/p>\n\n\n\n<p>For example, SAP Leonardo and Salesforce Einstein integrate AI seamlessly into enterprise resource planning (ERP) and customer relationship management (CRM) platforms, making AI a natural extension of daily operations.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"fa7bfd1c-d241-46cc-af7e-8234e79c3c09\"><span id=\"5-establish-rigorous-governance-and-review-protocols\"><strong>5. Establish Rigorous Governance and Review Protocols<\/strong><\/span><\/h3>\n\n\n\n<p>Define clear policies for reviewing AI-generated content, particularly for generative AI models that produce customer-facing materials. Implement access controls to restrict who can modify or deploy AI models, and continuously monitor usage patterns.&nbsp;<\/p>\n\n\n\n<p>Tools like IBM Watson OpenScale help in establishing fairness and transparency in AI operations, while Azure AI offers built-in governance tools to ensure compliance and security.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"3572fbb6-049e-4060-8a29-14b9e64120aa\"><span id=\"6-build-multi%e2%80%91disciplinary-teams\"><strong>6. Build Multi\u2011Disciplinary Teams<\/strong><\/span><\/h3>\n\n\n\n<p>AI success requires collaboration across cross-functional teams, including data engineers, domain experts, compliance officers, and business analysts. This ensures that AI initiatives meet both technical specifications and operational needs.&nbsp;<\/p>\n\n\n\n<p>For example, a team comprising an AI architect, a data scientist, and a legal advisor will ensure models comply with ethical standards and align with business goals.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"33f594f9-f528-4e46-b8bd-58ce11ef4d51\"><span id=\"7-track-outcome-metrics-continuously\"><strong>7. Track Outcome Metrics Continuously<\/strong><\/span><\/h3>\n\n\n\n<p>Set specific, measurable KPIs at the outset, such as accuracy, cost savings, speed improvements, or customer satisfaction. Track these metrics rigorously to ensure that the AI initiative delivers the expected benefits.&nbsp;<\/p>\n\n\n\n<p>Tools such as Tableau and Power BI can help visualise AI performance metrics, facilitating data-driven real-time adjustments.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"ad49db37-6431-482e-8964-3d6b7380e4a8\"><span id=\"codewave-practical-value-for-ai-and-enterprise-technology-projects\"><strong>Codewave: Practical Value for AI and Enterprise Technology Projects<\/strong><\/span><\/h2>\n\n\n\n<p>As companies evaluate how to integrate AI and generative AI into their operations, choosing the right partner can make a measurable difference. <a target=\"_blank\" rel=\"noreferrer noopener\" href=\"https:\/\/codewave.com\/\"><strong><u>Codewave<\/u><\/strong><\/a> is a design thinking\u2013led digital transformation company with a focus on tailored AI and software solutions that align with enterprise requirements.<\/p>\n\n\n\n<p>Here\u2019s how Codewave supports business outcomes in AI and technology initiatives:<\/p>\n\n\n\n<ul>\n<li><strong>Tailored AI Solution Design<\/strong> \u2013 Codewave builds custom AI systems that are built to address your specific business challenges rather than generic use cases, including predictive analytics, CX automation, and AI\u2011driven decision support.<\/li>\n\n\n\n<li><strong>Generative AI Services<\/strong> \u2013 Through its generative AI offerings, Codewave can create solutions that automate content workflows, enhance customer engagement, and generate real\u2011time insights, customized to your data and operational needs.<\/li>\n\n\n\n<li><strong>Integration with Existing Systems<\/strong> \u2013 The team ensures AI systems integrate seamlessly into enterprise technology stacks, supporting platforms such as CRM, ERP, data warehouses, and cloud systems without disrupting existing workflows.<\/li>\n\n\n\n<li><strong>Design Thinking Approach<\/strong> \u2013 By placing user experience and business outcomes at the core of solution design, Codewave helps organisations define clear objectives, establish success metrics, and minimise the risk of mismatches between technology and business strategy.<\/li>\n\n\n\n<li><strong>Cross\u2011Industry Expertise<\/strong> \u2013 With experience across sectors including healthcare, retail, fintech, energy, and education, Codewave applies context\u2011aware AI capabilities tailored to industry needs.<\/li>\n<\/ul>\n\n\n\n<p><a target=\"_blank\" rel=\"noreferrer noopener\" href=\"https:\/\/works.codewave.com\/portfolio\/\"><strong><u>Explore the Codewave portfolio<\/u><\/strong><\/a> to see examples of scalable solutions, spanning UX\/UI design, AI and machine learning, and web and mobile application delivery.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"6ade25ae-f396-4788-9ff7-7dfdc5e6cec0\"><span id=\"conclsuion\"><strong>Conclsuion<\/strong><\/span><\/h2>\n\n\n\n<p>Understanding the distinction between traditional AI and generative AI enables precise, purposeful evaluation of technology investments. AI models enhance decision support, automate repetitive processes, and improve forecasting. Meanwhile, generative AI expands your capacity to produce tailored content, accelerates knowledge work, and augments creative outputs.&nbsp;<\/p>\n\n\n\n<p>Successful implementations focus less on hype and more on integration with business goals, data governance, and outcomes tied to measurable KPIs rather than abstract promises.&nbsp;<\/p>\n\n\n\n<p>With careful strategy and execution, these technologies can drive measurable improvements across functions. If you\u2019re ready to use both AI and generative AI to solve real business problems and drive impact, explore how <a target=\"_blank\" rel=\"noreferrer noopener\" href=\"https:\/\/codewave.com\/\"><strong><u>Codewave<\/u><\/strong><\/a> can help you design and deploy the right solutions for your enterprise needs.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"e4f9ff0a-5bb3-46c8-8e8b-419313787b9e\"><span id=\"faqs\"><strong>FAQs<\/strong><\/span><\/h2>\n\n\n\n<p><strong>Q: Can generative AI create completely original ideas independent of its training data?<\/strong><br>A: Generative AI doesn\u2019t generate ideas in isolation. It produces new outputs by analysing patterns in its training data and recombining elements. Authentic creativity still depends on careful prompt design, custom fine\u2011tuning, and domain\u2011specific datasets to avoid repetitive or misleading results.<\/p>\n\n\n\n<p><strong>Q: What environmental impact should companies consider when adopting large AI models?<\/strong><br>A: Training and running large models, especially generative AI, require significant computational power, which can lead to high energy use and increased carbon emissions if not managed with efficiency strategies like optimized infrastructure or green data centers.<\/p>\n\n\n\n<p><strong>Q: How can organizations manage the risk of employees using unauthorized AI tools?<\/strong><br>A: Without clear policies, employees often use unapproved AI tools with sensitive data, leading to compliance issues. Establish AI usage guidelines, approved tool lists, and regular audits to prevent data leakage and ensure tools meet security standards.<\/p>\n\n\n\n<p><strong>Q: Does generative AI replace human judgment in business decisions?<\/strong><br>A: Generative AI can enhance the decision process by summarizing or drafting content, but it cannot replace human judgment for strategic or high\u2011stakes decisions because models can produce inaccuracies (so\u2011called <em>hallucinations<\/em>) and require context awareness that only humans provide.<\/p>\n\n\n\n<p><strong>Q: How should enterprises prepare for generative AI beyond technology deployment?<\/strong><br>A: Adoption requires not just tools but policy frameworks, compliance oversight, ethical standards, and ongoing education across teams to balance innovation with risk management and trust in outputs.&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"Explore the key differences between AI and Generative AI. Understand how Gen AI creates new content, while AI focuses on problem-solving and decision-making.\n","protected":false},"author":25,"featured_media":7985,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"csco_singular_sidebar":"","csco_page_header_type":"","csco_page_load_nextpost":"","csco_post_video_location":[],"csco_post_video_url":"","csco_post_video_bg_start_time":0,"csco_post_video_bg_end_time":0,"footnotes":""},"categories":[31],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v24.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Understanding AI vs. Generative AI for Enterprises -<\/title>\n<meta name=\"description\" content=\"Explore the key differences between AI and Generative AI. Understand how Gen AI creates new content, while AI focuses on problem-solving and decision-making.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/codewave.com\/insights\/understanding-ai-vs-generative-ai-differences\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Understanding AI vs. Generative AI for Enterprises -\" \/>\n<meta property=\"og:description\" content=\"Explore the key differences between AI and Generative AI. Understand how Gen AI creates new content, while AI focuses on problem-solving and decision-making.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/codewave.com\/insights\/understanding-ai-vs-generative-ai-differences\/\" \/>\n<meta property=\"article:published_time\" content=\"2026-01-29T13:39:46+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-01-29T13:39:48+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/codewave.com\/insights\/wp-content\/uploads\/2026\/01\/fb974257-e0ba-40f2-8f8c-292f9c6de331.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1456\" \/>\n\t<meta property=\"og:image:height\" content=\"816\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Codewave\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Codewave\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"14 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/codewave.com\/insights\/understanding-ai-vs-generative-ai-differences\/\",\"url\":\"https:\/\/codewave.com\/insights\/understanding-ai-vs-generative-ai-differences\/\",\"name\":\"Understanding AI vs. Generative AI for Enterprises -\",\"isPartOf\":{\"@id\":\"https:\/\/codewave.com\/insights\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/codewave.com\/insights\/understanding-ai-vs-generative-ai-differences\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/codewave.com\/insights\/understanding-ai-vs-generative-ai-differences\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/codewave.com\/insights\/wp-content\/uploads\/2026\/01\/fb974257-e0ba-40f2-8f8c-292f9c6de331.png\",\"datePublished\":\"2026-01-29T13:39:46+00:00\",\"dateModified\":\"2026-01-29T13:39:48+00:00\",\"author\":{\"@id\":\"https:\/\/codewave.com\/insights\/#\/schema\/person\/9463605ddab8f7088d98b8157c45b218\"},\"description\":\"Explore the key differences between AI and Generative AI. Understand how Gen AI creates new content, while AI focuses on problem-solving and decision-making.\",\"breadcrumb\":{\"@id\":\"https:\/\/codewave.com\/insights\/understanding-ai-vs-generative-ai-differences\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/codewave.com\/insights\/understanding-ai-vs-generative-ai-differences\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/codewave.com\/insights\/understanding-ai-vs-generative-ai-differences\/#primaryimage\",\"url\":\"https:\/\/codewave.com\/insights\/wp-content\/uploads\/2026\/01\/fb974257-e0ba-40f2-8f8c-292f9c6de331.png\",\"contentUrl\":\"https:\/\/codewave.com\/insights\/wp-content\/uploads\/2026\/01\/fb974257-e0ba-40f2-8f8c-292f9c6de331.png\",\"width\":1456,\"height\":816,\"caption\":\"Understanding AI vs. Generative AI for Enterprises\"},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/codewave.com\/insights\/understanding-ai-vs-generative-ai-differences\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/codewave.com\/insights\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Understanding AI vs. Generative AI for Enterprises\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/codewave.com\/insights\/#website\",\"url\":\"https:\/\/codewave.com\/insights\/\",\"name\":\"\",\"description\":\"Innovate with tech, design, culture\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/codewave.com\/insights\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/codewave.com\/insights\/#\/schema\/person\/9463605ddab8f7088d98b8157c45b218\",\"name\":\"Codewave\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/codewave.com\/insights\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/secure.gravatar.com\/avatar\/a78aa5a81c4b3d87f17a40eef3c3cb84?s=96&d=mm&r=g\",\"contentUrl\":\"https:\/\/secure.gravatar.com\/avatar\/a78aa5a81c4b3d87f17a40eef3c3cb84?s=96&d=mm&r=g\",\"caption\":\"Codewave\"},\"description\":\"Codewave\u00a0is a UX first design thinking &amp; digital transformation services company, designing &amp; engineering innovative mobile apps, cloud, &amp; edge solutions.\",\"url\":\"https:\/\/codewave.com\/insights\/author\/admin\/\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Understanding AI vs. Generative AI for Enterprises -","description":"Explore the key differences between AI and Generative AI. Understand how Gen AI creates new content, while AI focuses on problem-solving and decision-making.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/codewave.com\/insights\/understanding-ai-vs-generative-ai-differences\/","og_locale":"en_US","og_type":"article","og_title":"Understanding AI vs. Generative AI for Enterprises -","og_description":"Explore the key differences between AI and Generative AI. Understand how Gen AI creates new content, while AI focuses on problem-solving and decision-making.","og_url":"https:\/\/codewave.com\/insights\/understanding-ai-vs-generative-ai-differences\/","article_published_time":"2026-01-29T13:39:46+00:00","article_modified_time":"2026-01-29T13:39:48+00:00","og_image":[{"width":1456,"height":816,"url":"https:\/\/codewave.com\/insights\/wp-content\/uploads\/2026\/01\/fb974257-e0ba-40f2-8f8c-292f9c6de331.png","type":"image\/png"}],"author":"Codewave","twitter_card":"summary_large_image","twitter_misc":{"Written by":"Codewave","Est. reading time":"14 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/codewave.com\/insights\/understanding-ai-vs-generative-ai-differences\/","url":"https:\/\/codewave.com\/insights\/understanding-ai-vs-generative-ai-differences\/","name":"Understanding AI vs. Generative AI for Enterprises -","isPartOf":{"@id":"https:\/\/codewave.com\/insights\/#website"},"primaryImageOfPage":{"@id":"https:\/\/codewave.com\/insights\/understanding-ai-vs-generative-ai-differences\/#primaryimage"},"image":{"@id":"https:\/\/codewave.com\/insights\/understanding-ai-vs-generative-ai-differences\/#primaryimage"},"thumbnailUrl":"https:\/\/codewave.com\/insights\/wp-content\/uploads\/2026\/01\/fb974257-e0ba-40f2-8f8c-292f9c6de331.png","datePublished":"2026-01-29T13:39:46+00:00","dateModified":"2026-01-29T13:39:48+00:00","author":{"@id":"https:\/\/codewave.com\/insights\/#\/schema\/person\/9463605ddab8f7088d98b8157c45b218"},"description":"Explore the key differences between AI and Generative AI. Understand how Gen AI creates new content, while AI focuses on problem-solving and decision-making.","breadcrumb":{"@id":"https:\/\/codewave.com\/insights\/understanding-ai-vs-generative-ai-differences\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/codewave.com\/insights\/understanding-ai-vs-generative-ai-differences\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/codewave.com\/insights\/understanding-ai-vs-generative-ai-differences\/#primaryimage","url":"https:\/\/codewave.com\/insights\/wp-content\/uploads\/2026\/01\/fb974257-e0ba-40f2-8f8c-292f9c6de331.png","contentUrl":"https:\/\/codewave.com\/insights\/wp-content\/uploads\/2026\/01\/fb974257-e0ba-40f2-8f8c-292f9c6de331.png","width":1456,"height":816,"caption":"Understanding AI vs. Generative AI for Enterprises"},{"@type":"BreadcrumbList","@id":"https:\/\/codewave.com\/insights\/understanding-ai-vs-generative-ai-differences\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/codewave.com\/insights\/"},{"@type":"ListItem","position":2,"name":"Understanding AI vs. Generative AI for Enterprises"}]},{"@type":"WebSite","@id":"https:\/\/codewave.com\/insights\/#website","url":"https:\/\/codewave.com\/insights\/","name":"","description":"Innovate with tech, design, culture","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/codewave.com\/insights\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Person","@id":"https:\/\/codewave.com\/insights\/#\/schema\/person\/9463605ddab8f7088d98b8157c45b218","name":"Codewave","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/codewave.com\/insights\/#\/schema\/person\/image\/","url":"https:\/\/secure.gravatar.com\/avatar\/a78aa5a81c4b3d87f17a40eef3c3cb84?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/a78aa5a81c4b3d87f17a40eef3c3cb84?s=96&d=mm&r=g","caption":"Codewave"},"description":"Codewave\u00a0is a UX first design thinking &amp; digital transformation services company, designing &amp; engineering innovative mobile apps, cloud, &amp; edge solutions.","url":"https:\/\/codewave.com\/insights\/author\/admin\/"}]}},"featured_image_src":"https:\/\/codewave.com\/insights\/wp-content\/uploads\/2026\/01\/fb974257-e0ba-40f2-8f8c-292f9c6de331-600x400.png","featured_image_src_square":"https:\/\/codewave.com\/insights\/wp-content\/uploads\/2026\/01\/fb974257-e0ba-40f2-8f8c-292f9c6de331-600x600.png","author_info":{"display_name":"Codewave","author_link":"https:\/\/codewave.com\/insights\/author\/admin\/"},"_links":{"self":[{"href":"https:\/\/codewave.com\/insights\/wp-json\/wp\/v2\/posts\/7984"}],"collection":[{"href":"https:\/\/codewave.com\/insights\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/codewave.com\/insights\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/codewave.com\/insights\/wp-json\/wp\/v2\/users\/25"}],"replies":[{"embeddable":true,"href":"https:\/\/codewave.com\/insights\/wp-json\/wp\/v2\/comments?post=7984"}],"version-history":[{"count":1,"href":"https:\/\/codewave.com\/insights\/wp-json\/wp\/v2\/posts\/7984\/revisions"}],"predecessor-version":[{"id":7986,"href":"https:\/\/codewave.com\/insights\/wp-json\/wp\/v2\/posts\/7984\/revisions\/7986"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/codewave.com\/insights\/wp-json\/wp\/v2\/media\/7985"}],"wp:attachment":[{"href":"https:\/\/codewave.com\/insights\/wp-json\/wp\/v2\/media?parent=7984"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/codewave.com\/insights\/wp-json\/wp\/v2\/categories?post=7984"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/codewave.com\/insights\/wp-json\/wp\/v2\/tags?post=7984"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}