From AI to Analytics:
Technology and the Public Sector

From AI to Analytics: Technology and the Public Sector 2From AI to Analytics: Technology and the Public Sector 2
As governments work to transform and reshape public services, what are the
technologies that can help?
Robot Process Automation
Artificial Intelligence Cloud
Cyber
Data Digital Twin
Predictive Analytics
Digital Transformation

From AI to Analytics: Technology and the Public Sector 3From AI to Analytics: Technology and the Public Sector 3
Robot Process Automation
RPA is a software tool that can replicate and automate transactional processes while improving process
accuracy and speed.
It enables organisations to free up capacity to tackle their tactical priorities, which is why it is a key technology
for the public sector.
Robots are
Computer coded software
Programmes that replace humans
performing repetitive rules-based tasks
Cross-functional and cross-application
macros
Robots are not
Walking, talking auto-bots
Physically existing machines processing
papers
Artificial intelligence or voice recognition
and reply software

From AI to Analytics: Technology and the Public Sector 4From AI to Analytics: Technology and the Public Sector 4
RPA opportunities in the public sector
Central Government. Universal Credit
and benefits calculations, tax
calculations, anti-fraud checks, licensing
applications processing.
Local Government. Revenue collection,
permit applications, incident reporting,
case management, contract
administration.
Policing. Fixed penalty processing,
intelligence reporting, crime reporting,
firearms licence processing.
Health. Coding, diagnostics, discharge
processing, outpatient clinic outcomes.
Education. Managing admissions and
enrolments, student timetabling and
estates utilisation, student finance
management.
Explore insights
Report: The new machinery of government (See page 4 for a case study with the UK police force)
Insight: The robots are waiting

From AI to Analytics: Technology and the Public Sector 5From AI to Analytics: Technology and the Public Sector 5
Artificial Intelligence
AI can perform complex tasks at a level often equal to or surpassing humans, at scale.
The growing toolkit of AI (computer vision, natural conversation, and machines that learn over time) has the
potential to enhance almost everything government does, from education and health care to policing and
defence.
Government can use AI to deliver human services in three main areas
Predicting fraud
and abuse
Back-office
Customer
engagement
Mission-focused
Automating
determination of
eligibility
Inspection and
enforcement
Setting up
outcome-based
programs
Disease
surveillance
Addressing
queries of
caseworkers
Personalising
service delivery
through machine
learning
Real-time language
translation
Addressing
queries by
chatbot
Auto-filling
application forms
Integrating multiple
programs
Scheduling
appointments
Automating
verification
Automating
documentation and
reporting

From AI to Analytics: Technology and the Public Sector 6From AI to Analytics: Technology and the Public Sector 6
An integrated AI strategy considers technology and management choices
Explore insights
Article: 6 areas for assessing AI readiness in government
Article: AI augmented government
Article: Crafting an AI strategy for government leaders
Case Study: Using artificial intelligence to save money and improve patient care in an NHS Trust
Vision
What is our level of AI
ambition
Focus
Where should we
concentrate our
AI investment?
Success
How will AI
development
create value
Capabilities
What do we need
to execute our
AI strategy?
Management
systems
What systems will
implement and
manage AI
Management
What should operating,
governance, and change
management approaches be?
Technology
What platform data and
other technical changes
are needed?
Management
How will value be
define/measured? How
will ethics be addressed?
Technology
Which AI technologies
and what level of human
involvement are needed?
WHAT IS INTEGRATED AI STRATEGY?
Technology
How should the tech stack,
data, and scale-up be
managed?
Management
What people, partners
and organizational
changes are needed?
Technology
How mature/complex are
solutions? How will they
be piloted and scaled?
Management
Which applications
processes, or problems
should we consider?

From AI to Analytics: Technology and the Public Sector 7From AI to Analytics: Technology and the Public Sector 7
Digital Transformation
Public sector organisations are embracing digital transformation to make it easier for citizens to interact with
them. Whether it’s filing and paying taxes online, renewing a passport, or registering to vote – offering services
online means they can be provided quicker and at a lower cost, saving citizens time and helping government get
the most out of finite budgets.
Government reimagined through digital can:
Improve
processes
Engage talent across
the organisation
Drive new and value-generating
service models for citizen

From AI to Analytics: Technology and the Public Sector 8From AI to Analytics: Technology and the Public Sector 8
Digital Transformation
Explore insights
Article: Keeping pace? Government’s technology transformation
Article: The digital citizen
Perspective: Digital Government Transformation
Leadership
A digitally sophisticated leadership team
that understands new age trends,
technologies and their benefits is a game-
changer in an organisation’s digital
transformation.
Strategy
Have a roadmap to address all the key elements
of digital transformation, then develop a clear
strategy that moves beyond efficiency to focus
on fundamental transformation of citizen
services.
Workforce development
Digital skills go beyond mere technical
ones. Look at new sources of talent and
build a workplace that offers an experience
in line with the aspirations of millennials.
Culture
Build a culture that allows room for risk-taking
collaboration and innovation. Also learn to
employ digital trends and technologies to
reinforce such a culture.
User focus
A key tenant of digital delivery is to start with
the user. Develop engagement plans for
users that ‘attract’ ‘engage’ and ‘extend and
employ inherently user-centric agile
development methodologies’.

From AI to Analytics: Technology and the Public Sector 9From AI to Analytics: Technology and the Public Sector 9
Data
Public sector data is becoming more important for many reasons. Public pressure for transparency and
accountability is mounting. Many are calling on governments to leverage data to gain greater insights and
formulate better policies. And data can offer new ways to curb waste, fraud, and abuse, as well as to operate
more efficiently and get more done with less.
The importance of data in government
Where can data help?
• Effectiveness: “Do what we do
better”
• Efficiency: “Do more with less”
• Fraud, waste and abuse: “Find and
prevent leakage”
• Transparency and citizen
engagement: “Build trust”
Why is data important?
• Public demand for transparency and accountability
• Increased access to large amounts of data
• Responsibility of data security
• Technology innovation and exponential disruptors driving added
complexity
• Changing citizen needs and preferences
• Budget constraints driving the need for greater operational efficiency
• Responsibility to limit fraud, waste and abuse

From AI to Analytics: Technology and the Public Sector 10From AI to Analytics: Technology and the Public Sector 10
Explore insights
Article: Turning public data to the public good
Article: Data as an asset
Article: The rise of data and AI ethics
Article: Data tokenisation for government
To be successful in this effort, leaders must have a nuanced understanding of the organisation’s current data
culture, resources, and opportunities for improvement. By carefully selecting and implementing a data strategy
and capitalising on victories, data leaders can position their organisations for success in making use of data as a
valuable strategic asset.
Where to begin:
Defining a data
strategy with success
in mind
How to implement a
data strategy: Turning
a document into a
movement
Tailor to the organisation’s unique
needs and align with the overall
mission and goals.
Consider the human side: owners,
stakeholders, analysts, and other
users. Engage all parts of the
organisation from day one.
Keep it flexible. It is imperative to
plan and establish a strategy that
accounts for future changes.
It’s helpful to start with high-
visibility projects that draw on key
components of the data strategy.
You can improve the chances of a
project’s success by developing
partnerships across the
organisation. Once the solution is
deployed, everyone can declare
victory.
Success breeds success, and you
should capitalise on every victory,
pointing to them when making a
budgetary case for additional
resources, technologies, or
capabilities.
Data

From AI to Analytics: Technology and the Public Sector 11From AI to Analytics: Technology and the Public Sector 11
Predictive Analytics
Explore insights
Insight collection: Analytics
Article: Anticipatory government
Case Study: Predictive analytics in health care
​The idea that government should focus more on preventing problems than just reacting to them is not new.
Today, advances in predictive analytics allow more governments to work toward pre-empting problems.
HOW CAN PREDICTIVE ANALYTICS BE USED IN THE PUBLIC SECTOR?
Reduce crime.
Some global police forces are using AI
to observe patterns in criminal activities
and identify hotspots with a high
incidence of crime, allowing for quicker
interventions.
Predict cyberattacks.
Predictive analytics can sift through a
large set of data to identify malicious
code, anomalous patterns, and network
threats to help predict cyberattacks.
Counter terrorism.
The European Union’s Horizon 2020
program launched an initiative called
RED Alert, aimed at countering
terrorism by monitoring social media
conversations posted by extremists.

From AI to Analytics: Technology and the Public Sector 12From AI to Analytics: Technology and the Public Sector 12
Cloud
The cloud offers scope
for a more responsive,
flexible approach to
delivering online services
– enabling government
departments to innovate
in ways that were once
beyond their reach.
Now governments across
the globe are adopting
cloud-first policies to
spur innovation and
improve services for
citizens, enabling cloud
to become the
foundation for emerging
technologies such as AI,
robotic process
automation, and data
analytics.
COST SAVINGS TOP THE LIST OF GOVERNMENT ORGANISATIONS’
REASONS TO MOVE TO THE CLOUD
In your opinion, what are the priority factors driving your organisation’s adoption of
cloud technologies?
8%
10%
14%
17%
18%
32%
34%
34%
34%
42%
43%
45%
Source: Government business Council and Deloitte, channeling
the cloud, December 2017
Note: N = 282
None of the
above
Other
Growth of internet of
things/devices
Improvements in
advanced analytics
Potential for increase innovation
Enhanced data security
Data center consolidation
Increase mission effectiveness
Increase adaptability/flexibility
Expanded data-sharing capabilities
Improved organizational efficiency
Cost reductions/savings

From AI to Analytics: Technology and the Public Sector 13From AI to Analytics: Technology and the Public Sector 13
Five recommendations to move forward
Introduce cloud-focused policies that go
beyond location and vendor details to
define and measure how all of the
organisation’s policies will help it better
accomplish its mission.
Break data silos by making data more
organised, standardised, and accessible
across the agency.
Focus on innovation capabilities enabled
by cloud, and work with your cloud
vendor to gain access to the right types
of tools and capabilities.
Understand and define the spectrum of
identity access management and ask
questions such as “who owns what
data?” and “who can access it?” for each
application.
Understand the organisational changes
the shift to cloud might demand and
make a deliberate change management
plan.
Explore insights
Guide: Cloud fluency guide
Article: Cloud as innovation driver
Article: The switch to cloud - how public services are becoming more agile and innovative
Case Study: How Cloud technology is helping DVSA keep Britain’s roads safe
01 02
03 04
05

From AI to Analytics: Technology and the Public Sector 14From AI to Analytics: Technology and the Public Sector 14
Cyber
As the world becomes smaller, cyber is getting bigger. Cyber risk is at the centre of digital transformation.
Understanding that is as transformative as cyber itself—and to be successful in this new era, organisations
should embrace a “cyber everywhere” mentality.
Cyber requires more executive attention,
budget, prioritisation, people, tools,
processes, governance, and overall
collective thought.
Cyber needs a leader with the authority
to drive change.
Cyber will require organisations to
become more nimble, more flexible, and
more collaborative as they work to
secure their organisations, their
employees, their customers, and
partners.
Data complexities will continue to
challenge many organisations.
Automation, speed, and insights will
power the future of cyber.
01 02
03 04
05
FIVE RECOMMENDATIONS FOR TACKLING THE CYBER DEMANDS OF THE FUTURE

From AI to Analytics: Technology and the Public Sector 15From AI to Analytics: Technology and the Public Sector 15
To make sure you are protecting what's most important to your business, ask
yourself these key cyber questions:
Explore insights
Practical guide: Questions to ask yourself about cyber
Article: Ransoming government
Article: Why cybersecurity presents the public sector with an opportunity to innovate
Report: The future of cyber survey
Case Study: 24 hours inside a cyber attack
How do we manage
third party risk?
What do we need to
protect the most?
Do we have the right
skills?
Do we have the
appropriate security
measures in place?
What is our cyber risk
management setup?
Is cyber security
embedded in our
business?
What is the likely
threat?
What if the worst
happens?

From AI to Analytics: Technology and the Public Sector 16From AI to Analytics: Technology and the Public Sector 16
Digital Twin
Explore insights
Article: Convergence of technology in government
Article: Industry 4.0 and the digital twin
Case Study: Policing 4.0
A digital twin is an evolving digital profile of the historical and current behaviour of a physical object or process
that helps optimise business performance. It is the exact digital replica of a physical entity, bringing the benefits
of digital analysis to the physical world.
Health care:
Optimisation of
hospital life cycles.
Urban development:
Optimisation and risk-
free testing.
Police force: Develop
insight on where to
invest new resources.
DIGITAL TWIN APPLICATIONS INCLUDE

From AI to Analytics: Technology and the Public Sector 17
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