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Descr.Fascicoli:Vol.105, 2000$fC $h20071018$i20121204$cVol.96, 1999$d 52PER.STR. 163$e 52VP 0000179285 VP Inventario:21050FLS Descr.Fascicoli:Vol.96, 1999$fC $h20071018$i20121204$cVol.99, 1999$d 52PER.STR. 163$e 52VP 0000179275 VP Inventario:20485FLS Descr.Fascicoli:Vol.99, 1999$fC $h20071018$i20121204$cVol.98, 1999$d 52PER.STR. 163$e 52VP 0000179265 VP Inventario:20484FLS Descr.Fascicoli:Vol.98, 1999$fC $h20071018$i20121204$cVol.101, 1999$d 52PER.STR. 163$e 52VP 0000179255 VP Inventario:20483FLS Descr.Fascicoli:Vol.101, 1999$fC $h20071018$i20121204 977 $a 52 996 $aProceedings of the British Academy$9894011 997 $aUNICAS LEADER 07127nam 22007215 450 001 996565863303316 005 20231115135337.0 010 $a3-031-29053-4 024 7 $a10.1007/978-3-031-29053-4 035 $a(MiAaPQ)EBC30949288 035 $a(Au-PeEL)EBL30949288 035 $a(DE-He213)978-3-031-29053-4 035 $a(EXLCZ)9928861780700041 100 $a20231115d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 14$aThe AI-Enabled Enterprise$b[electronic resource] /$fby Vinay Kulkarni, Sreedhar Reddy, Tony Clark, Henderik A. Proper 205 $a1st ed. 2023. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023. 215 $a1 online resource (144 pages) 225 1 $aThe Enterprise Engineering Series,$x1867-8939 311 08$aPrint version: Kulkarni, Vinay The AI-Enabled Enterprise Cham : Springer International Publishing AG,c2023 9783031290527 327 $aIntro -- Preface -- Contents -- About the Authors -- 1: The AI-Enabled Enterprise -- Motivation -- Current State -- Decision-Making in the Face of Uncertainty -- Software Architecture for Continuous Adaptation -- Automated Compliance with Minimal Exposure to Risk -- Democratized Knowledge-Guided Software Development -- Continuously Adapting Software -- Coordinated Continuous Digital Transformation -- The AI-Enabled Enterprise -- Illustrative Example -- References -- 2: Decision-Making in the Face of Uncertainty -- Introduction -- Current Practice -- Decision-Making as an Optimization Problem -- Model-Based Decision-Making -- Human-Centric Decision-Making -- Solution -- Decision-Making Meta-Model -- Digital Twin -- ``In Silico´´ Experimentation Aid for Decision-Making -- Technology Infrastructure -- Specification Language -- DT Construction -- DT Validation -- Illustrative Real-World Applications -- Case Study from Telecom -- Maximizing Throughput of Sorting Terminals -- Optimizing Shop Stock Replenishment for a Retail Chain -- Prediction and Control of Covid-19 Pandemic in a City -- Helping Organizations Transition from Work from Home to Work from Office Mode -- Summary and Future Work -- References -- 3: Regulatory Compliance at Optimal Cost with Minimum Exposure to Risk -- Introduction -- Regulatory Compliance -- Current Practice -- Tenets of a Desirable Line of Attack -- AI-Aided Model-Based Automated Regulatory Compliance -- Technology Infrastructure to Support the Line of Attack -- AI-Based Model Authoring -- Validating the Authored Model -- Automating Compliance Checking -- Benefits of the Proposed Approach -- Illustrative Use Cases of Automated Regulatory Compliance -- Assurance of Hygiene -- Business Problem -- Scope -- Approach -- Benefits -- Compliance Hygiene and Change Impact Management -- Business Problem -- Objectives -- Scope. 327 $aApproach -- Benefits -- Compliance Checking -- Business Problem -- Current Practice -- Objectives -- Scope -- Approach -- Benefits -- Change Management -- Business Problem -- Scope -- Approach -- Results -- Benefits -- Summary and Future Work -- References -- 4: Continuously Adapting Software -- Introduction -- Digital Twin(s) -- State of the Art -- Modelling Twin Systems -- Case Study -- Twin System Execution -- Twin Policies -- Implementation: TwinSim -- Training for Multiple Eventualities -- Prototyping as Part of the Development Process -- Research Roadmap -- References -- 5: Democratized Hyper-automated Software Development -- Introduction -- Current Practice -- Typical SDLC Today -- Model-Driven Development -- Low-Code/No-Code Platforms -- AI-Powered SDLC -- AI-Powered Requirements -- AI-Powered Testing -- AI-Powered Coding -- Proposed Line of Attack -- Knowledge-Guided, AI-Aided Refinement of Business Requirements into Software Requirements -- Domain Ontology -- Systems Knowledge -- AI and NLP -- Digital Twin(s) -- Knowledge-Guided, AI-Aided Refinement of Software Requirements into Software Specifications -- Architecture for Software Adaptation -- Technology Infrastructure to Support the Line of Attack -- References -- 6: Coordinated Continuous Digital Transformation -- Introduction -- Digital Transformation -- Continuous Digital Transformation -- Coordinated Continuous Digital Transformation -- Enterprise Design Dialogues -- The Role of Models -- Challenges and Opportunities -- Conclusion -- References -- 7: A Case Study: Wellness Ecosystem -- Introduction -- Wellness Ecosystem -- Wellness Stakeholders -- Individual -- Gym -- Food Store -- Hospital -- Insurance Company -- Leisure Provider -- Wellness Provider -- Decision-Making in Dynamic and Uncertain Environment -- Effecting the Decisions in Software. 327 $aEffecting the Decisions in Business Processes -- Bringing It All Together -- Illustrative Example -- References. 330 $aThe AI enabled enterprise uses technology to continuously learn by monitoring its behavior and the environment as well as external knowledge sources in order to automate the decision-making and decision-implementation processes leading to continuous improvement over time. This book discusses the key challenges that organizations need to overcome in achieving an AI enabled enterprise: the role of digital twins in evidence-backed design, enterprise cartography that goes far beyond process mining, decision-making in the face of uncertainty, software architecture for continuous adaptation, democratized knowledge-guided software development enabling coordinated design, low code versus no code, and coherent design. For each challenge, the book proposes a line of attack along with the associated enabling technology and illustrates the same through a near real world use case. 410 0$aThe Enterprise Engineering Series,$x1867-8939 606 $aBusiness$xData processing 606 $aBusiness information services 606 $aMachine learning 606 $aInformation technology$xManagement 606 $aArtificial intelligence 606 $aBusiness Informatics 606 $aEnterprise Architecture 606 $aMachine Learning 606 $aComputer Application in Administrative Data Processing 606 $aArtificial Intelligence 615 0$aBusiness$xData processing. 615 0$aBusiness information services. 615 0$aMachine learning. 615 0$aInformation technology$xManagement. 615 0$aArtificial intelligence. 615 14$aBusiness Informatics. 615 24$aEnterprise Architecture. 615 24$aMachine Learning. 615 24$aComputer Application in Administrative Data Processing. 615 24$aArtificial Intelligence. 676 $a650.0285 676 $a658.05 700 $aKulkarni$b Vinay$01448645 701 $aReddy$b Sreedhar$01448646 701 $aClark$b Tony$01448647 701 $aProper$b Henderik A$01367069 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996565863303316 996 $aThe AI-Enabled Enterprise$93644349 997 $aUNISA