AI as a Business Driver

Transcription

1 AI as a Business Driver Bled, Lada Banić, Lead Consultant, lada.banic@inteligencija.com

2 1 Company profile

3 WHY? It is not that important WHAT we are doing, more important is WHY we are doing that. We are devoted to implementation of analytical solutions for decades and we have strong dedication to make our customers most successful global companies in their industries.

4 COMPANY PROFILE CROATIA Leading DW/BI vendor in SEE 200+ delivered projects 80+ customers in 20 countries 130+ employees 100+ consultants 75 technical 20 business 5 project managers More than 800 Man/Years experience with leading tehnologies Leading partners SERBIA MONTENEGRO SLOVENIA BOSNIA 2010 UK 2011 Austria

5 Communications Finance Retail & Distribution Manufacturing High Tech Utility & service

6 PRIZES AND AWARDS ICT GOLD AWARD 2016 In category Business Intelligence for the solution Analytics at the palm of your hand for best and most innovative ICT solution implemented at ORBICO GROUP Expert level in Data Science, Business Analytics and Hybrid Data Management competencies

7 OUR SOLUTION AREAS Strategic ICT consulting Business Intelligence Data Warehouse Planning & Budgeting Predictive modeling Data Quality Data Governance Balanced Scorecard MDM Data Integration Analysis, design, development, implementation, support and education Big Data Intelligent Data Security

8 2 AI as a Business Driver

9 Wording and meaning Data mining (DM) finds patterns in data Machine learning (ML) predicts future Artificial intelligence (AI) enables computer to think (uses ML to reason about the world and give rise to intelligent behavior)

10 ML/AI new era 50 years ago knowledge was coded now learning by example RECOGNITION OF S

11 ML RECOGNITION OF S

12 ML

13 ML NOT

14 ML NOT

15 Different aspects of ML Supervised learning Unsupervised learning Reinforcement learning

16 AI in business Big data examples Online shopping recommendations Driver-less cars Facebook sugestions for interesting content Voice recognition in smartphones Photographs that become purchases (amazon image search on mobiles) Etc. Performance improving examples: Fraud claims in insurance and similar fields Customers behavior insight Diseases diagnosing in healthcare Price optimization for products and services Etc.

17 Jobs AI can do better than humans Take long time Tedious Involve lots of data (even more than human brain can process/ that is difficult for human brain to process) Repetitive Low level tasks Jobs that burden humans Andrew Ng, the Stanford professor: If a typical person can do a mental task with less than one second of thought, we can probably automate it using AI either now or in the near future.

18 Jobs AI can t do better than humans Communication Empathy Creativity Strategic thinking Questioning Dreaming

19 Changes derived by ML Tasks and occupations Business processes Business models

20 Limitations of using ML Low interpretability Large number of parameters that lead to decision Hidden biases in training data Statistical truth

21 Benefits of using ML Process large amounts od data in short time Make predictions and forecasts Performing repetitive tasks without errors Increased productivity Process efficiency Optimization of activity

22 Barriers in AI implementation Lack of understanding Unrealistic expectations Expense Technology Change

23 Prerequsites for AI implementation Type of work that AI can perform Algorithms Data quantity Industry digitalization Data quality

24 How to start Do not start big but bring benefit Realistic expectations Do not seek perfection Do not give up on obstacles Be critical, ask questions Be opened to unexpected findings Embrace change

25 Questions

26 Thank you