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Applying AI & Search in Europe - featuring 451 Research

In the current climate, it’s now more important than ever to digitally enable your workforce and customers.
Hear from Simon Taylor, VP Global Partners & Alliances, Lucidworks and Matt Aslett, Research Vice President, 451 Research to get the inside scoop on how industry leaders in Europe are developing and executing their digital transformation strategies.
In this webinar, we’ll discuss:
The top challenges and aspirations European business and technology leaders are solving using AI and search technology
Which search and AI use cases are making the biggest impact in industries such as finance, healthcare, retail and energy in Europe
What technology buyers should look for when evaluating AI and search solutions

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Applying AI & Search in Europe - featuring 451 Research

  1. 1. 1 Applying AI & Search in Europe – Featuring 451 Analyst
  2. 2. 2 Todays Speakers Simon Taylor VP Global Partners & Alliances Lucidworks Matt Aslett Research Vice President 451 Research
  3. 3. 3 Search & AI Application in the Current Pandemic Where to Focus to ease the Burden of doing Business
  4. 4. 4 We’re now living in a different world… G E N E R A L T R E N D S * o 48% of the market is still formulating its digital transformation planning o 89% of consumers are concerned with protecting their personal data online: Covid-19 bad actors o 76% of consumers are likely to switch to an alternate online vendor: poor experience / Covid-19 o 47% of digitally aware consumers would prefer virtual assistants to save time vs. call center N E E D S * o Measure digital performance relative to the customer experience o Improve personalised digital experiences for content and commerce along with customer data and intelligence platforms o Use of virtual assistants to ease capacity issues relative to accessing relevant information and deflection of expensive call service interactions o Improve employee information access in the new “Working from home” situation *451 Research, LLC – Copyright, March 2020
  5. 5. TRANSITIONING TO A VIRTUAL DIGITAL WORKPLACE IS CHALLENGING
  6. 6. 78% of businesses believe Covid-19 has already had a negative operational impact. 75% already have or will be implementing expanded work-from-home policies in response to the crisis 38% that think work-from-home policies will become be long-term or made permanent. 62% have already experienced a fall in employee productivity, or expect to in the next three months. 41% report having already felt an internal strain on their IT resources. 22% have delayed/halted rolling out of new products or services. Coronavirus quick fixes aren’t scalable; business leaders must rethink work itself | 451 Group Research March 20th , 2020
  7. 7. Top Priorities ACHIEVE A UNIFIED SINGLE SOURCE OF INFORMATION [INC. CUSTOMER DATA] GAIN RICHER SOURCES OF DATA FOR LINE OF BUSINESS DECISION MAKERS Voice of The Enterprise: Workforce Productivity & Collaboration, Employee Lifecycle | 451 Group Research, Q2 2019
  8. 8. We need to connect people to data insight? Predictable, organisationally defined data access BEFORE Empowered data consumers seek insight and drive productivity on their own NOW
  9. 9. Data Scientist Driven Activity Business Alignment Meet the “Last Mile Problem” BigDataManagement &Analytics ❶ ❷ ❸ ❹ ❺ ❻ ❼ ❽ Problems with Activating Data for Digital Transformation
  10. 10. Data Scientist Driven The Last Mile Problem Reduced Time to Value Quantifiable & Faster ROI Search,Discovery& OperationalAI BigDataManagement &Analytics ❶ ❷ ❸ ❹ ❺ ❻ ❼ ❽ ❶ ❷ ❸ ❹ Direct Alignment with Business Needs Problems with Activating Data for Digital Transformation
  11. 11. The Digital Transformation Question? To AI or not to AI?
  12. 12. What goes wrong with AI in Digital Transformation Projects?  BAD DATA IN = BAD RECOMMENDATION OUT. FALSE POSITIVES REDUCING CONFIDENCE IN MACHINE LEARNING  LONGER TERM COMPLACENT DEPENDENCIES ON “INFALLIBLE” MACHINE LEARNING  IN ABILITY FOR AI TO TAKE ACCOUNT OF THE WIDER CONTEXT OF BUSINESS NEEDS / OUTCOMES
  13. 13. Challenges Adopting AI & ML IT Teams May misunderstand both the business objectives and the machine learning model. Business Leaders Define the business goals that want to pursue with AI, but they don’t usually understand the challenges and limitations of building ML models Data Scientists Understand machine learning, but they might not truly understand the business objectives and they may build “hungry” models that consume too many IT resources 1 2 3
  14. 14. Artificial Narrow Intelligence (ANI) is the AI that exists in our world today, programmed to perform a single task —  whether it’s checking the weather, being able to play chess, or analyzing raw data to to write journalistic reports. Artificial General intelligence (AGI) or refers to machines that exhibit human intelligence. In other words, AGI can successfully perform any intellectual task that a human being can being conscious, sentient, and driven by emotion and self-awareness. ANI systems can process data and complete tasks at a significantly quicker pace than any human being can, which has enabled us to improve our overall productivity, efficiency, and quality of life e.g. assist doctors to make data-driven decisions, making healthcare better AGI is expected to be able to reason, solve problems, make judgements under uncertainty, plan, learn, integrate prior knowledge in decision-making, and be innovative, imaginative and creative. It’s all about Operationalising AI
  15. 15. “Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.” SAS INSTITUTE INC. 2019
  16. 16. How to Implement Machine Learning A FRAMEWORK FOR APPLYING AI IN THE ENTERPRISE GARTNER INC. 2017
  17. 17. ML-Powered Search Learning Maturity Self-Learning Taxonomies/Entity Extraction Automated Relevancy Tuning Query Intent Prediction Keyword Search
  18. 18. Many AI tools’ designs start with just data, not the human question. Thus, a great AI platform focuses on an answer to the question by using search, rather than just being tool based. AI AUTHORITY CHAO HAN, HEAD OF DATA SCIENCE, LUCIDWORKS SEPT 2018
  19. 19. FILTER VISUALIZATION ACTIVITY CONTENT INDEX NATURAL LANGUAGE BOOSTED RESULTS MACHINE LEARNING QUERY RULE MATCHING USER SIGNALS FACET, TOPIC & CLUSTER D ATA Human Generated System Generated Application Generated S O L U T I O N Digital Workplace NATURAL LANGUAGE MACHINE LEARNING QUERY RULE MATCHING USER SIGNALS FACET, TOPIC & CLUSTER
  20. 20. 20 HYPER PERSONALISATION Go beyond using static rules and profiles. Instead dynamically customise the experience for each data consumer. Use AI and machine learning to predict user intent and give employees the insights they need, when they need them. Maximise the opportunities to tailor content that fits each and every employee’s wants and needs. Explore Curate Integrate MACHINE LEARNING
  21. 21. Use Case Examples Digital Commerce Predictive Merchandising Catalog Search Sentiment Analysis Personal Assistant/Chatbots Digital Workplace Scientific Research Call Center Prioritisation Support Deflection Natural Language Search Fraud Detection
  22. 22. Advanced connectors and AI enrichment, delivered by intuitive applications created with App Studio, deployed on-prem or as a multi-tenant cloud managed service. D ATA Any format, any platform S O L U T I O N Personalised insights for each individual STORAGE & SEARCH INTENT PREDICTIO N APP CREATION DATA INGEST & PREP F U S I O N P L AT F O R M Human Generated System Generated Application Generated Digital Workplace
  23. 23. STORAGE & SEARCH INTENT PREDICTION APP CREATIONDATA INGEST & PREP NLP: NER, phrases, POS Document classification Anomaly detection Clustering Topic detection Search engine & data processing Connectors ETL pipelines Scheduling & alerting SQL engine Rules engine Query pipelines Query intent detector Automatic relevancy Signals & query analytics Recommenders A/B testing Modular components Stateless architecture User-focused experience Geospatial mapping Results preview Rapid prototyping S C A L A B L E O P E R AT I O N S SECURITYCDCRCLOUDSCALABLEEXTENSIBLE
  24. 24. ML for Anomaly Detection on Data Ingest
  25. 25. Signals ML for Query Rule Rewrite
  26. 26. D ATA Any format, any platform Human Generated System Generated Application Generated Index Search Intent BuildApp S O L U T I O N A S S E M B LY Digital Workplace RULE ENTITY ML NLP BOOST SIGNAL R A P I D A S S E M B LY P L AT F O R M FUSION Q&A Chatbot FUSION Risk Analysis FUSION Workplace Search S O L U T I O N T E M P L AT E S
  27. 27. R E A L - L I F E E X A M P L E S Lucidworks Fusion powers connected experiences Customer Care Investigation Employee Q&A Supply Efficiency Compliance & Audit
  28. 28. C A S E S T U D Y Single, global source of truth in their knowledge management application An accurate picture of client interactions and expertise Content disambiguation 10MD O C U M E N T S M A N A G E D 40KEMPLOYEES
  29. 29. C A S E S T U D Y Better customer support Putting the right information in front of customers in fewer clicks Improved support calls Shorter wait times, and a more engaged support Reinvest savings 200%I N C R E A S E I N C T R 50KF E W E R S U P P O R T T I C K E T S 34%C A L L D E F L E C T I O N 91%R E D U C T I O N I N T C O
  30. 30. C A S E S T U D Y More searches converted into sold tickets Full-site search on iOS & Android mobile apps 33%I N C R E A S E I N C O N V E R S I O N 63%I M P R O V E M E N T I N V I S I T O R S 15%R E V E N U E AT T R I B U T E D T O S E A R C H
  31. 31. 31 Q&A
  32. 32. 32 THANK YOU Get In Touch! Email: teameurope@lucidworks.com

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In the current climate, it’s now more important than ever to digitally enable your workforce and customers. Hear from Simon Taylor, VP Global Partners & Alliances, Lucidworks and Matt Aslett, Research Vice President, 451 Research to get the inside scoop on how industry leaders in Europe are developing and executing their digital transformation strategies. In this webinar, we’ll discuss: The top challenges and aspirations European business and technology leaders are solving using AI and search technology Which search and AI use cases are making the biggest impact in industries such as finance, healthcare, retail and energy in Europe What technology buyers should look for when evaluating AI and search solutions

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