This document discusses how organizations can prepare for artificial intelligence (AI) and the importance of data and machine learning. It provides examples of banks investing in AI and digital technologies. Sections include discussions of data science, different types of machine learning techniques (supervised, unsupervised, reinforcement, semi-supervised), and the need for data governance, skilled talent, and executive leadership to fully leverage AI.

1. 1
How to ready your
organization for AI
March 2017
C 2017

2. 2
Realization that we are all data and
technology companies…
…that offer data centric products and services…
C 2017

3. 3
Is Data the “Next Element”?
…reinterpret all business activities through the prism of
data: the fuel and the organizing vision that will drive
business in the future….
Enrique Dans 2017
C 2017

4. 4
The world has changed…
…AI is already affecting the world…the potential of new machine-
learning technology is so much greater…
…Soon, we will see safe driverless cars, life-saving medical advances
and the Internet of Things. All powered by AI technology.
Jonathan Schaeffer 2017
C 2017

5. 5
The Last 90 Days
C 2017

6. 6
Inside the Royal
Bank of Canada’s
machine-learning
labs
Scotiabank Deploys Deep
Learning to Improve Credit
Card Collections
Can RBC help
Stop Canada's
brain drain in
deep learning?
RBC wants 40%
of total
technology
budget
devoted to
innovation
-As Fintech fears fade, Canada’s
banks look to next big thing:
Artificial Intelligence
-Meet the new Canadian banker:
The tech rockstars who are taking
over Bay Street
-RBC to boost focus on AI with
new research lab
Scotiabank to invest
$1 billion in digital
The Great A.I. Awakening
How Google used artificial
intelligence to transform
Google Translate and how
machine learning is poised to
reinvent computing itself
C 2017

7. 7
Sun Life’s chief digital technology
officer readies for Silicon Valley-
inspired HQ launch
DMZ launches
insurtech accelerator
program with Aviva
Canada
Sun Life feels ready
for oncoming
“insurtech”
Manulife double
down on AI,
Blockchain
This is an insurance office? A
look inside Aviva’s ‘Digital
Garage’ in the sky
C 2017

8. 8
Venture Scanner 2017
C 2017

9. 9
Changing Landscape
C 2017

10. 10
Decision Management
Open Data
Graph Analytics
Citizen Data Science
Data Ethics
Analytics Governance
Algorithmic Business
Blockchain
Data as a Service
Notebooks
Python
Deep Learning
Deep Neural Nets
Text Analytics
Video Analytics
Scala
Machine Learning
Data Science
Data Lakes
Information Architecture
Python
GPU
Master Data Management
Cloud
Spark
Hadoop
In-Memory Processing
R
Event Processing
Natural Language Processing
Speech Analytics
Natural Language Generation
Data Catalogues
Info. Lifecycle
ManagementData
Security & Privacy
Database
Management
DB
Data Integration
Data
Services
Data Quality
Customer
Innovation
Reference DataMetadata
Dashboards
Advanced Analytics
Data Governance
C 2017

11. 11
Gartner 2017
C 2017

12. 12
Gartner 2017
C 2017

13. 13
Where are you on the journey?
C 2017

14. 14
Reporting
Business
Intelligence
Data
Warehouse
2009
Hadoop
Batch
2011
Real-Time
Data Lake
2015
Machine
Learning
Deep Learning
Cognitive
Client Interaction
+2016
Data Science
Data Science
C 2017

15. 15
Evolving
Organizations that
have some advanced
data science skills.
Leading Edge
Organizations that are
leading deep-learning
research, strategy and
innovation
Advanced
Organizations that
leverage vendors to for
deep learning, machine
learning, AI
Starting Line
Limited Understanding:
Predictive Analytics, AI,
Machine-Learning and
Deep Learning??
C 2017

16. 16
UnSupervised
Find structure from unknown
data
Find patterns in unlabeled and
unstructured data
Reinforcement
Experience driven sequential
decision making
Machine learning from
actions/decisions based on
Correct/ Incorrect actions
Semi-Supervised
Mix of Supervised/unsupervised
learning
Mix of labeled/non-labeled data
Non-Determined Features
Supervised
Mapping input to output
Labeled Data
Pre-Determined Features
C 2017
Learning Technique: Shallow
Algorithms with few layers Small Data Sets, Limited Complexity
Learning Technique: Deep
Layers of neural networks. Large Data Sets, High Complexity Outcome
Computer Vision
Ability to discern images
within images video and still
Natural Language
Processing
Natural Language Understanding
Natural Language Generation

17. 17Business Value
AnalyticalMaturity
Data
Governance Metadata
Data
Quality
Strategic Importance
Machine
Learning
Deep Learning
Cognitive
Client Interaction
Forecastingand
Probabilities
Business
Intelligence
Advanced
Analytics
Descriptive
Diagnostic
Predictive
Reporting
Data Science
Forecasting and
Probabilities
Forecasting and
Probabilities
C 2017

18. 18
Enablement
C 2017

19. 19
Top Down Leadership
Chief Data Officer
CEO
Chief Analytics
Officer
Chief AI
Officer
Chief Digital
Officer
CIO
Machine
Learning
Deep LearningCognitiveClient Interaction
Data Science
C 2017

20. 20
Data 101
Data
Governance Metadata
Data
Quality Data Catalogue
Machine
Learning
Deep Learning
Cognitive Client Interaction
Data Science
Reporting
Business
Intelligence
Advanced
Analytics
C 2017

21. DeliveryTesting
Data
Modeling
Data
Exploration
Data Prep
Data
Collection
Business
21
Team Sport
Chief Data Officer CIO Lob Executive
Data Science Data Engineer Project ManagerBusiness SME Data Architect
21C 2017

22. 22
Embrace Complexity
Data ScienceReporting
Business
Intelligence
Advanced
Analytics
Machine
Learning Deep Learning Cognitive Client InteractionInnovation Cloud GPU vs CPU
C 2017

23. 23
Questions
C 2017

24. 24
Artificial Intelligence, Banking, Big Data,
Business Analytics, Business
Architecture, Business Capability,
Business Intelligence, Business
Leadership Business Process, Business
Transformation, Chat Bots, Chief Data
Architect, Cloud, Customer Centricity,
Customer Relationship Management ,
Data Architecture , Data Assessments,
Data Governance, Data Integration,
Data Process Modeling, Data Quality,
Data Science, Data Strategy,, Data
Visualization, Data Warehouse, Design,
Deep Learning, Financial Services,
Enterprise Architecture, FSLDM,
Hadoop, Information Lifecycle
Management, Investment, Machine
Learning, Master Data Management,
Metadata Management, Mobile, Next
Generation Data Platform, Open Data,
Open Source, Python, R, Reference
Data Management, Roadmap, Risk
Management, Spark, Startup,
Technology Stack, Thought Leadership
Craig C. Milroy
@craigmilroy
ca.linkedin.com/in/craigcmilroy
C 2017