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