Emerging TechnologiesFuture Scan v2.0

This future scan provides a big picture view of maturing, scaling and emerging technologies that are helping organizations drive innovation, change and agility in today's increasingly competitive marketplace.

MET

HODOLOGIE

S

Expe

rienc

e

Agile

DevOps

Cloud Native

Mobile SolutionsAugmented Reality

Advanced AnalyticsVideo Analytics

Artificial Intelligence

Digital Twins

IoT

HPC

Cyber Security

Blockchain

Inno

vatio

n M

anag

emen

t

Des

ign

Intelligent Automation

Maturing

Scaling

Emerging

Maturing

Scaling

Emerging

Cre

ativ

e

Technical

Channels Data-Driven

Sensors & Automation

Computing & Infrastructure

Security

TECHNOLOGIES

• A

I-po

wer

ed in

nova

tion

• S

usta

inab

le in

nova

tion

• In

nova

tion

sprin

ts

• In

nova

tion

cultu

re

embe

dded

in th

e

orga

niza

tion

• C

row

d in

nova

tion

• D

ata-

driv

en

inno

vatio

n

• D

esig

n th

inki

ng/h

uman

-cen

tere

d

desi

gn

• H

acka

thon

s

• B

uyin

g in

nova

tive

star

t-up

s

• In

nova

tion

stud

ios

/ la

bs

• A

I as

desi

gner

• La

b as

a s

ervi

ce

• In

nova

tion

Day

• M

icro

-ser

vice

s fro

nt e

nds

• B

usin

ess

desi

gn•

Des

ign

syst

em•

Dat

a th

inki

ng•

Dat

a-dr

iven

des

ign

• C

onve

rsat

iona

l UI

• M

otio

n de

sign

• U

I des

ign

• D

iagn

ostic

an

alyt

ics

• D

esig

n th

inki

ng• A

gile

SA

Fe

• W

eb U

X

• A

cces

sibi

lity

desi

gn• R

emot

e re

al-t

ime

colla

bora

tion

•AI I

oT ro

botic

sup

ervi

sion

• U

X fo

r AR

/ VR

• P

WA

(SPA

)

• U

X fo

r voi

ce, g

estu

re

• O

rg. d

esig

n

• XR

des

ign

• S

EO +

UX

= S

XO

• C

ultu

re d

esig

n

• D

esig

nOps

• M

ood

as in

terfa

ce

• H

aptic

feed

back

(des

ign)

• Di

gitiz

atio

n

of c

onte

nt

• O

mni

-cha

nnel

• In

tera

ctiv

e ob

ject

s

• Vo

ice

inte

ract

ion

• C

hatb

ots

(nar

row

AI)

• C

onte

xtua

l mes

sagi

ng (n

arro

w A

I)

• (B

road

AI)

inte

ract

ion

• Au

gmen

ted

expe

rienc

e

• Sm

art m

ater

ials

• M

obilit

y

• Bus

iness

agil

ity

• Citiz

en se

rvice

s agil

ity

• Dat

a go

vern

ance

stra

tegie

s

(GDPR, e

tc.)

• Ser

vice

desig

n / d

esign

think

ing

• Agil

e co

ntra

cting

• Sca

ling

agile

• Agil

e HR

• Tea

m-le

vel a

gile

• Scr

um

• Kan

ban

• Lea

n po

rtfoli

o

man

agem

ent

• Dev

Ops /

DeveS

ecOps

• Clou

d na

tive

deve

lopm

ent

• Virtu

al AI s

oftware engineers

• Failu

re injectio

n (e.g.,

“Chaos M

onkey” by

Net�ix)

• AI /

self-h

ealing

• Toolchain orchestr

ation

• Release

automation

• Low code / n

o code

• Microse

rvices

• Cloud nativ

e

development /

PaaS

• DevS

ecOps

• Agile m

ethods

/ Lean

• Infra

structure

as code

• Virtu

alizatio

n

• Release

automation

• SaaS

• Contin

uous

integration (C

I)

/ Contin

uous

delivery

(CD)

• IaaS cloud

• Containeriz

ation and sc

aling

• Serve

rless

computing

• Cloud-enabled data modernization

• Micro-service maturity

patterns

• Agile

• Orchestration• OS abstraction• Move to

micro-services• Softw

are-de�ned

networking

• DevOps

• API exposure

• Virtual m

achines

• Open source

• PaaS

• Cloud

• Containers

• Testing

• Framework

• Operational integration

• Cloud native security

• Service meshes• Distributed services

• Patterns

• Sensor-based, real-time data

streams and services

• X-platforms

- Xamarin

- RX Java

- React Native

• Arti�cial intelligence /

machine learning

• Personalization

• Kotlin

• Swift

• Voice

• Responsive web

• Objective C

• Java

• Progressive web app (PWA)

• X-platform ionic

• Advanced analytics

• Complex of�ine application

• Super-personalization

• IoT identities (IAM)

• 5G

• X-platform �utter

• Human machine interfaces

• Augmented reality

• Wearables• Blockchain / DLT

• Digital companion

• Virtual retina display (VRD)

• AI and machine

Learning in AR

• Hardware miniaturization

• Logistics use cases

• Training use cases

• Manufacturing use cases

• Retail use cases

• AR headsets

• Gaming AR

• Affordable hardware

• Interaction / collaboration

use cases

• Data connectivity / 5G

• AR apps

• Digital twin

• AR in cars

• Edge computing

• AR contact lenses

• Eye tap

• Traditional BI reporting

• Enterprise data hub/data lake, data warehouse

• Assisted analytics(data quality / auto curation)

• Cognitive analytics (broad AI)

• Data as a product/data partnership

• Contextual data analytics(social, voice, video, image, location, IoT)

• Proliferation of metadata management

• Predictive and prescriptive analytics

• Data visualization / mobile dashboards

• Interactive / self-service analytics / BI

• Data governance strategies (GDPR, etc.)

• Data cloud storage and analysis

• Automated analytics(narrow AI)

• Deep neural networks

• Data curation

• Descriptive analytics

• Diagnostic analytics

• Video analytics as a service

• Video algorithms in the cloud

• Value-added subscriptions

• Crowd analytics

• Video compression

• Non-visible light spectrum

• Complex object recognition

• Distributed algorithms (edge, on premise, cloud)

• AI neural networks for video analytics

• Industry 4.0

• 3D modelling (AR / VR)

• Supervised training (machine learning)

• Simple object recognition

• OCR

• Facial recognition

• Facial analytics

• Safety and security

• Autonomous driving

• Automated video annotation

• Unsupervised training (machine learning)

• Behavioral analytics

• Arti�cial General Intelligence (AGI)

• Unsupervised learning /

Deep neural networks• Adversarial machine

learning

• Auto machine learning

• Democratized AI

• Data curation

• Reinforcement learning

• Explainable AI

• Ethics in AI

• Applied AI / arti�cial narrow intelligence (ANI)

• Supervised learning

• Brain-computer interface (BCI)

• Self-aware AI

• Edge AI / Distributed AI• Quantum computing

• AI arms race

• Augmentend reality + digital twin

• Holographic digital twins

• Machine learning

• 3D printing

• Open APIs

• Geospatial information

systems (GIS)• Manufacturing

execution systems (MES)

• PLM / PDM /

CAD systems

• Predictive analytics

• Big data lakes

• 3D models

• 5G connectivity• Consumer IoT

• Sensor data

• Industrial IoT

• Space and drone data

• Real-time maps

• Digital mirror world

(e.g., "The Matrix")

• IoT platform offerings specialized in

design and operate scenarios

• Processing and analysis

of data moved to edge

of network

• Interactive objects /

voice-based services

• Mobile platforms for

management of IoT

devices• Industry and public

sector use cases

• IoT advanced analytics

• IoT data visualization

• IoT-enabled

automation

• Public cloud IoT

platform services

• IoT security

• Machine-to-

machine

• Mobility

• Intelligent and autonomous

devices

• IoT business scale• Smart materials

• Automating interactions,

judgment, em

pathy, sentiment

• Contextual data analytics

(social, voice, video,

image, location, IoT)

• RPA integrated with

advanced analytics /

narrow AI

• Basic virtual agents

with human back-up

• Video / image analytics

• Complex process /

transaction automation

• Deep learning / neural

networks / narrow AI

• Speech recognition

/ natural language

processing

• Supervised

machine

learning

• RPA (simple,

rules-based)• Clerical work

automation

• Text-based,

scripted

chatbots

• Cognitive / broader AI / deep

neural networks

• Fully autonomous virtual agents

• RPA + process mining

• Quantum

computing

• General AI

• Business digital assistance / AI

• Deep neural networks /

application-speci�c

integrated circuit (ASIC)

• Augmented and virtual

reality (AR / VR)• Serverless

infrastructure

• Com

posable

infrastructure

• Hyper

converged

infrastructure

• Hyperscale

public clouds

• Grid

computing

• Autonomous cars

• GDPR• 5G

• Quantum

encryption

• Field programm

able gate

array (FPGA) chips

• Graphic processing unit

(GPU

) / holographic

processing unit (HPU

)

• Automated AI-based response

• Intelligence-driven security

monitoring / m

achine

learning / narrow AI

• Critical infrastructure /

IoT security

• IT + OT convergence

• Proactive threat

hunting

• Supply chain

security

• Netw

ork-centric

perimeter

security

• Reactive,

siloed

cybersecurity

• Identity

managem

ent

• Malw

are

protection

• Intrusion

detection /

prevention• Digital

forensics

• Holistic threat surface

defence

• Ransom

ware

• Cloud, m

obile device

security

• Gov’t regulation

(e.g., GD

PR)

• Proactive threat hunting

• Cybersecurity bots

• DevSec O

ps• AI-driven attacks

• Security of autonomous AI

systems

• Social in�uencing meddling /

dis-information

• Security schem

e for distributed

devices in a network

• Industrialized / scaled blockchain

• Blockchain as a service

• Maintaining personal

identity across accounts

• Exchange of big data

• Blockchain proof of

concepts

• Blockchain labs

• Settlem

ent applications

• Trade-based applications• Transactional applications

• Governm

ent research• Asset tracking

• Digital

currencies

• Bitcoin

• Sm

art contract

framew

ork

• Energy applications

• Blockchain consortium

s

• GD

PR

solutions• P

rivacy by design

• Business applications using public

blockchains