{"id":22846,"date":"2024-04-11T15:41:18","date_gmt":"2024-04-11T14:41:18","guid":{"rendered":"https:\/\/www.avolutionsoftware.com\/?p=22846"},"modified":"2024-05-09T21:45:20","modified_gmt":"2024-05-09T20:45:20","slug":"how-artificial-intelligence-ai-supercharges-enterprise-architecture","status":"publish","type":"post","link":"https:\/\/www.avolutionsoftware.com\/news\/how-artificial-intelligence-ai-supercharges-enterprise-architecture\/","title":{"rendered":"How Artificial Intelligence (AI) can Supercharge Your Enterprise Architecture"},"content":{"rendered":"

Enterprises are\u00a0in the midst of\u00a0an application explosion and a transformation acceleration.\u00a0This means\u00a0\u00a0their underpinning\u00a0architectures\u00a0\u2013 made up\u00a0of\u00a0interactions between\u00a0people,\u00a0processes\u00a0and technology\u00a0\u2013 are growing and changing more quickly than ever.\u00a0These all\u00a0need\u00a0regular oversight and management.<\/strong><\/p>\n

What kind of organization and decision-making challenges are we looking at? Well, let\u2019s consider just cloud applications. According to Gartner’s forecast on public cloud end-user spending<\/a>, the worldwide end-user spending on public cloud services is forecast to grow 20.4% to total $678.8 billion in 2024i<\/sup><\/span>.\u00a0Cloud now represents\u00a0around a half of all\u00a0IT\u00a0infrastructure;\u00a0with\u00a0cloud migration also continuing\u00a0apace.<\/p>\n

As well as the\u00a0layers of\u00a0infrastructure,\u00a0servers,\u00a0bespoke\u00a0software\u00a0and off-the-shelf solutions\u00a0which keep a business humming,\u00a0enterprise\u00a0architects\u00a0also manage\u00a0how these interact with external systems, with\u00a0processes,\u00a0with people and\u00a0the\u00a0numerous\u00a0documents and data sources\u00a0that go with these.<\/p>\n

Large amounts\u00a0of\u00a0technical and\u00a0financial\u00a0data\u00a0are\u00a0also\u00a0continually\u00a0generated.\u00a0Big data keeps getting bigger.\u00a0All this\u00a0needs\u00a0sensible monitoring\u00a0as\u00a0significant costs and risks are at stake: the job of architects.<\/p>\n

 <\/p>\n

How can AI help Enterprise Architects?<\/h2>\n

Many companies\u00a0are\u00a0already\u00a0comfortable\u00a0relying\u00a0on\u00a0Artificial Intelligence (AI) or machine learning to\u00a0boost\u00a0business data\u00a0analysis\u00a0or sales workflows. For\u00a0instance,\u00a0as part of\u00a0their CRM, or their cybersecurity\u00a0defenses.<\/p>\n

A 2024 report by Forbes<\/a> found that over half of business owners are using artificial intelligence for cybersecurity<\/a> and to combat fraudii<\/sup><\/span>. Other top use-cases include improving internal communications and customer relationships.<\/p>\n

We can also use AI\u00a0to quickly generate insights from other enterprise datasets.<\/p>\n

Enterprise architects\u00a0who\u00a0need\u00a0to\u00a0identify\u00a0trends, bottlenecks\u00a0and\u00a0opportunities\u00a0are turning to\u00a0tools\u00a0including\u00a0algorithms, artificial intelligence and machine learning\u00a0to\u00a0get their arms around\u00a0their technical datasets\u00a0and\u00a0business\u00a0strategy.<\/p>\n

AI\u00a0also\u00a0allows architects to extract\u00a0an additional layer of\u00a0value\u00a0from the very\u00a0structure, connections<\/em>\u00a0and\u00a0complexity\u00a0<\/em>of the\u00a0architectures\u00a0they\u2019ve put time and effort into\u00a0documenting.<\/p>\n

They can use it to\u00a0draw information\u00a0from multiple layers of the enterprise\u00a0architecture<\/a>,\u00a0look for patterns\u00a0to \u2018fill in the blanks\u2019\u00a0and bring this\u00a0all\u00a0together\u00a0intelligently\u00a0into\u00a0straightforward, everyday\u00a0recommendations.<\/p>\n

Experts are also expecting AI to benefit from graph database\u00a0technology<\/a>;\u00a0as a \u00a0article in\u00a0Information Week\u00a0<\/em>explained\u00a0\u201cAI\u2019s future focuses on graph modeling. Graphs encode intelligence in the form of models that\u00a0describe the linked contexts<\/a>\u00a0within which intelligent decisions are executediii<\/sup><\/span>.\u201d<\/p>\n

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Faster Digital Business Decisions<\/h2>\n

AI is\u00a0math\u00a0not magic.\u00a0It is highly data-driven and based on patterns\u00a0and\u00a0relationships\u00a0in data.<\/p>\n

Upload a spreadsheet\u00a0of applications, lifecycles or financial data\u00a0and\u00a0link\u00a0in other\u00a0architectural content\u00a0in\u00a0ABACUS<\/a>\u00a0and the AI\/machine learning engine Ask ABACUS<\/em> will use this dataset to provide a quantitative prediction of the values which belong in any empty cells.\u00a0\u00a0For instance, if a cell for an application’s TIME recommendation (Tolerate, Invest, Migrate, Eliminate) is blank, Ask ABACUS<\/em> can suggest a recommendation.<\/p>\n

And in the example below, if we’re unsure which department owns or uses Application 944, Ask ABACUS<\/em> can analyze our data and suggest with over 96% confidence that it belongs to US-Department 11.<\/p>\n

\"Ask<\/em><\/p>\n

AI recommendation engine “Ask ABACUS” in the ABACUS enterprise architecture tool<\/em><\/p>\n

 <\/p>\n

AI Use Cases in Enterprise Architecture<\/h2>\n