{"id":53955,"date":"2024-03-06T16:43:30","date_gmt":"2024-03-06T21:43:30","guid":{"rendered":"https:\/\/sdtimes.com\/?p=53955"},"modified":"2024-03-06T16:47:21","modified_gmt":"2024-03-06T21:47:21","slug":"data-integration-and-alignment-will-dictate-generative-ais-impact-on-digital-transformation","status":"publish","type":"post","link":"https:\/\/sdtimes.com\/ai\/data-integration-and-alignment-will-dictate-generative-ais-impact-on-digital-transformation\/","title":{"rendered":"Data integration and alignment will dictate generative AI\u2019s impact on digital transformation"},"content":{"rendered":"

Generative AI has taken the enterprise world by storm throughout 2023 \u2013 and for good reason. From a digital transformation perspective, it has the potential to amplify efficiency to new heights at a time when it\u2019s needed most.<\/span><\/p>\n

Most enterprise digital transformation efforts today fail. A recent Gartner<\/span> report<\/span><\/a> found that nearly 70% of CFOs believe digital spending is underperforming against expected outcomes. The root cause is a disconnect between those outcomes and the software teams’ capacity to deliver them. Planview\u2019s independently commissioned<\/span> Project to Product 2023 State of the Industry Report<\/span><\/a> found that business leaders believe IT teams in charge of digital transformation efforts can deliver 10x more than their actual capacity. Only<\/span> 8% of IT and software development plans<\/span><\/a> are ultimately executed, while 40% of digital innovation work is wasted.<\/span><\/p>\n

The simple answer for this inefficiency is disconnected and disparate data. Most organizations leverage a plethora of tools to deliver digital transformation at scale. From Jira and GitHub to GitLab and Azure DevOps, these systems all play a critical role across the end-to-end software development lifecycle. But here\u2019s the catch \u2014 none of them are integrated or aligned. Value streams with minimal interoperability cause bottlenecks that hinder digital transformation from succeeding. Data integration and alignment is critical.<\/span><\/p>\n

Enterprise digital transformation is nearing a new era of opportunity amid the rise of generative AI. Because generative AI\u2019s large language models (LLMs) are domain agnostic and don\u2019t reside in any single system, it has unrivaled potential to minimize wasted workflows when integrated with Strategic Portfolio Management and Value Stream Management technologies. The global digital transformation market size is<\/span> expected to exceed<\/span><\/a> $7 trillion by 2032. Even a 5-to-10% reduction in waste is more than enough to move the needle. The time to act is now.<\/span><\/p>\n

Integration: A semantic foundation of data<\/b> \u00a0<\/span><\/h5>\n

Effectively harnessing generative AI\u2019s power to minimize wasted work first requires a common semantic layer of data. Fusing datasets from heterogeneous systems into a normalized data platform creates an essential foundation for optimizing the flow of value. Once that holistic data foundation is in place, organizations can then engineer prompts that train generative AI LLMs to produce impactful prescriptive insights, identify high-risk workflows, and refine resource allocations. This removes a lot of the drudgery from software team planning processes, essentially automating the fundamental aspects of value stream management with AI-powered productivity.<\/span><\/p>\n

Another prescription could be identifying various underlying dependencies between different product or project initiatives that are causing significant delays \u2014 leading the organization to add direct resource capacity or rebalance capacity between teams based on what the data is surfacing. This level of acute data-driven decision-making relative to capacity and allocation helps align financial investments to high-priority projects, accelerating time to market for initiatives with the greatest ROI.<\/span><\/p>\n

Alignment: The power of convergence<\/b><\/h5>\n

Organizational alignment is critical to leveraging generative AI for digital transformation success. It\u2019s important to remember that technology is only as powerful as your ability to deploy it. For generative AI to effectively accelerate value, it\u2019s imperative to eliminate<\/span> the \u201cblack box\u201d that exists<\/span><\/a> between business outcomes and software development. An organization\u2019s business and technology functions must be operating in unison. By synchronizing all the tools, processes and metrics associated with software development and delivery, organizations can optimize decision-making across portfolios, value streams and DevOps teams to link digital transformation capital allocation to impactful business outcomes.<\/span><\/p>\n

This is where converging objectives and key results (OKRs) across strategic portfolio management, value stream management, and agile planning are worth their weight in gold. It doesn\u2019t matter how brilliant the generative AI prompts are \u2013 they are incapable of achieving desired outcomes and driving digital transformation without a shared overarching mission. Universal alignment connects gaps between the technology and business facets of the organization with real-time visibility that provides more intelligence, predictions, and prescriptions. By integrating these actionable insights from portfolio management, enterprise agile planning, and value stream management into a single source of truth, a system of record, cross-functional teams have a clear roadmap for transforming ideas into outcomes.<\/span><\/p>\n

It\u2019s no secret that the ongoing generative AI hype over the past 10 months has sparked valid concerns about its ability to replace human workers across industries. However, in the context of digital transformation, we shouldn\u2019t think about the future with a narrow \u201chuman or machine\u201d mindset. It\u2019s really about humans <\/span>plus<\/span><\/i> machines. Applying AI-powered technology to augment manual workflows is what will deliver the greatest impact on digital innovation in the years to come.\u00a0<\/span><\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

Generative AI has taken the enterprise world by storm throughout 2023 \u2013 and for good reason. From a digital transformation perspective, it has the potential to amplify efficiency to new heights at a time when it\u2019s needed most. Most enterprise digital transformation efforts today fail. A recent Gartner report found that nearly 70% of CFOs … continue reading<\/a><\/p>\n","protected":false},"author":1213,"featured_media":53957,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"om_disable_all_campaigns":false,"cybocfi_hide_featured_image":"","footnotes":"","_links_to":"","_links_to_target":""},"categories":[1],"tags":[143,2850,16528,15620,12793],"coauthors":[16892],"acf":[],"yoast_head":"\nData integration and alignment will dictate generative AI\u2019s impact on digital transformation - SD Times<\/title>\n<meta name=\"description\" content=\"Effectively harnessing generative AI\u2019s power to minimize wasted work first requires a common semantic layer of data.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/sdtimes.com\/ai\/data-integration-and-alignment-will-dictate-generative-ais-impact-on-digital-transformation\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Data integration and alignment will dictate generative AI\u2019s impact on digital transformation - 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