Technology adoption paradigm is shifting rapidly. 2019 brings new hopes and opportunities around adoption of Machine Learning, Artificial Intelligence, Blockchain, Biometrics, etc. across IT initiatives. Here is brief overview of technology trends and adoption patterns in 2019 and beyond.

1. Technology adoption patterns & trends – 2019 and beyond…
Perspective and point of views around key technologies, their potential maturity journey throughout 2019
and typical adoption patterns across the enterprises.
Swarraj Kulkarni | swarraj@gmail.com | These are my personal thoughts & I do not represent any of my employers and clients - present or past.
Photo by Ales Nesetril on Unsplash

2. • Views expressed in this presentation are my own and I do NOT represent the views of any of my
employers or clients present or past.
• Publicly available information either from technology product vendors, Industry Analysts or from fellow
technologists is referred as appropriate to build these views or form opinions.
• I acknowledge their contributions and have mentioned specific / relevant sources in the slides as well
as in the reference section.
2

3. Context
Technology has been always considered as business enabler but
the attention it has gained in recent past is unimaginable. Art of
possibility and implementation feasibility of ideas which business
stakeholders discuss in the board rooms are being successfully
demonstrated as working POCs, MVPs and systems running in
production. Technologies and technology driven services are
creating opportunities for innovative business models, defining
new playbooks for customer interactions and building engaging
digital experiences for internal and external clients alike.
Gartner has projected global IT spending to be $3.8 trillion in
2019, an increase of 3.2% from expected spending of $3.7 trillion
in 2018. Gartner had also pointed out significant spending
patterns across projects in AI, ML, IOT, Big Data, Blockchain and
Digital projects which are main drivers of the growth.
Technology adoption paradigm is shifting rapidly. This shift is
being fueled either through never ending customer expectations
or growing pressure of applying levers to reduce operating cost
of IT functions. Customers are aware that their individual
attributes and behavior data is being used by businesses service
providers and expect highly sophisticated and hyper personalized
service in return at lower cost and in secure manner.
3
Organizations are harvesting and processing Terabytes of data to
decipher customer insights and building analytical models to give
improved customer experience. Deep learning techniques and AI
have made strides by proactively meeting customer expectations.
On the cost and operating efficiency front, Cloud has been
already adopted by businesses. Concerns around data security
and regulatory restrictions are fading away with significant pace.
Blockchain and smart contracts have gained significant traction in
last few years and 2018 has seen some serious adoption of it
across different domains. Cyber security and digital identity are
major concerns which are not just limited to individual
organizations but have reached to national level.
2018 has seen many of these technologies and adoption patterns
getting matured and crossing entry barriers. 2019 brings new
hopes and opportunities for improving established footprint and
implementing innovative use cases and at the same time push
back and tackle other challenges on the way. This brief
presentation is an attempt to highlight key paradigm shifts,
technology enhancements and adoption patterns we can expect
and experience in 2019.

4. Crossing the chasm : 2019 will be the year to make that transition
4
Innovators
Early
Adopters
Early
Majority
Late
Majority
Laggards
Chasm
In his book ‘Crossing the Chasm [1]’, Geoffrey Moore pointed out typical
technology adoption life cycle and the ‘chasm’, which is the phase between
technology early adoption and it’s majority adoption.
While many Digital technologies like Cloud, API, mobile, and Analytics have
reached certain maturity level and by now their adoption status across the
enterprises is either in ‘early majority’ or ‘late majority’, there are still few
promising technologies like Blockchain, ML/AI, biometrics and IOT where
exploration and experimentation is still going on. 2017 and 2018 seen some
‘early adoption’ with success, 2019 will see their transition across the chasm
and get them into ‘early majority’ adoption state. Highly regulated industries
like Banking and Insurance will continue to be cautious but aggressive in 2019.
Obviously to cross the chasm, enterprises need to identify valid business
scenarios and use cases, collaborate with partner ecosystems, educate and
engage with customers and expect support from the regulatory bodies. While
CIO/CTO organizations are investing into their internal innovation units, to
accelerate the process 2019 will see great traction and collaborations with
FinTech and RegTech.
It is equally important to review and validate completeness and functioning of
already adopted technology initiatives and their critical impacts on business
outcomes. 2019 will see greater focus on extracting learning from such
initiatives, standardization and resiliency improvements across the IT units.
Though many Digital technologies are in ’early majority’ or ‘late
majority’ adoption state, niche technologies like Blockchain, AI ,
advance biometrics and IOT are being experimented and expected to
cross the chasm in 2019…

5. Transformation Initiative’s alignment with business objectives &
impact on outcomes : Typical traits, sentiments & corrective actions
Initiative Outcomes Early Majority Late Majority
Overall Positive
+ Clarity in business vision and expected outcomes
+ Chosen valid business scenarios and use cases
+ Substantial investment in technology validation
+ Collaboration with internal / external tech SMEs
+ MVP and incremental approach involving business SMEs
+ Learned and followed early adopters
+ Followed set guidelines and best practices
+ Focused on differentiators on established tech stack
+ Onboarded SMEs with hands on experience
+ Substantial investments on proven tech stack/products
Neutral
o Need to validate expected outcomes and associated traceability
o Need to Review use cases and constrain overall scope
o Should involve business stakeholders and end customers
o Need additional time to collect data points
o Review tech stack, products and team skills
Overall Negative
- Need to review & alter business scenarios / use cases
- Need to optimize, fine tune technology investments
- Seek help from external SMEs & product vendors
- Need to focus on stakeholders / end users education
- Capture feedback from team on the ground
- Missed learnings from early adopters
- Redefine scope, value differentiation, priorities
- Consolidate & optimize tech stack
- Seek help from external SMEs & product vendors
- Success stories socialization w internal / external users
5
Digital rewards first movers and some superfast followers. They develop a learning advantage. They relentlessly test and learn, launch early prototypes, and refine results in real time.
They are often pushing ahead on version 3.0 or 4.0 offerings before followers have launched their “me too” version 1.0 : McKinsey.com – Why Digital Strategies fail [2]

6. In 2019, enterprises will continue exploration, adoption, review and
improvements across these key paradigms & technologies
6
Digital Enterprise
UX & Usability
Engineering
Cloud native
app dev
Public Cloud &
services
Digital Identity
& Biometrics
FinTech,
InsureTech
Machine Learning
& AI Blockchain
IOT / Smart
Sensors
Unlearning &
Learning
Next Gen
Programming
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7. 1. Enterprise UX & Usability Engineering will play critical role in being digital
• Next gen digital products and enterprise applications will cater to traditional desktop and
mobile devices as well as to the voice, AR/VR consoles, partner intelligent systems and IOT
interfaces. Role of Design Thinking (What Is–What If–What wows & –What works) will
become more significant in 2019.
• There will be significant advancements in UX maturity levels across serious ‘digital focused’
enterprise IT initiatives. These enterprises understand importance of UX and have senior
executive commitments and involvements in defining UX strategies over last few years.
• As presented by JJ Kercher [3], on the Johan Berndtsson’s UX maturity model these
enterprises will aim to achieve maturity level 5 (Engaged: UX is one of the core tenets of the
organization strategy) or level 6 ( Embedded: UX is in the fabric of the organization, not
discussed separately).
• Bringing balance between automated (pre-scripted) chatbots and insights/AI driven
intelligent conversation will be major focus for engaging end users and improving UX [4].
• Voice activated & voice command technologies will continue to grow [5]. By 2020 around
50% of search engine queries will be performed through voice commands. Voice User
Interfaces and Conversational AI (Amazon Alexa, Google Home) adoption across business
domains and scenarios will continue further.
• UX researchers will continue to demonstrate digital future capabilities and possibilities.
Questions around ROI on UX will get diluted with significant proofs and working MVPs. UX
researchers, UX engineers & UI developers will become an integral part of the strategy &
agile dev teams. Transition from just consultants to true change agents across initiatives.
• Enterprises will have holistic focus on ‘Usability Engineering’ with right level of involvement
from end clients and internal stakeholders at all levels and across all stages of UX lifecycle. 7
AI ML Preferences
Hyper personalization
AI ML Preferences
GUI / VUI
API / Integration Mechanism
Systems IOT
User centered design & intelligent Interaction
Domain context
Role based access & experience
Business Services
SORs / Data / Backend Systems
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8. 2. Cloud native app dev will become norm for almost all greenfield apps
• Enterprises adopted microservices, API & container technologies for green app development
as well as for app modernization purpose in 2017/18. Initial concerns and doubts around
scope and boundaries of bounded contexts, granularity of services, data architecture in new
paradigms and security have relatively faded out. Patterns and anti-patterns have established
themselves through successful implementations of several large scale complex programs.
• In 2019 and beyond, cloud native app dev will be a norm for almost all green field and app
modernization initiatives to be deployed either on private, hybrid or public Cloud.
• As pointed out in IBM’s 2018 research focused on the adoption of the cloud-native dev model
across 152 enterprises respondents [6], 55% of apps developed in next 12 months will be
designed as cloud-native. 75% of existing non-cloud apps will move to cloud environment in
the next 3 years. And 66% of companies overall are exploring cloud-native app development
model.
• According to Cloud Native Computing Foundation [7], use of cloud native technologies in
production has grown over 200% in 2018 itself. 40% of their survey respondents are running
Kubernetes in production. In 2019, this adoption will see new heights.
• DevOps assembly lines adoption will continue growing across enterprises. As architectures are
becoming micro, complexity will continue shifting towards process automation & tools.
• Based on Collabnet’s 12th ‘annual state of agile’ report [8] agile adoption across enterprises is
expanding with “all or almost all” teams on agile, there is still room for agile maturity.
Internal agile coaches, consistent practices and process across teams, implementation of
common tools are helping enterprises in scaling agile. Enterprises will continue this
momentum in 2019.
• Full Stack Developers with niche skills around technologies, tools and processes will be in high
demand. Agile Program managers, SCRUM Masters, Product Owners and FSDs will be key
resources for successful implementation & delivery of next gen cloud native digital products.
8
DevOps assembly lines
Container / PaaS Platforms
Microservice Microservice
Agile app
delivery
Highly available
Highly Scalable
Highly Performing
Modular & maintainable
Self healing capable
Resilient
Flexible
Support polyglot
Autonomous
Cloud native app typical characteristics
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9. 9
3. Public Cloud APIs & services to build enterprise apps will get accelerated
• Leading public cloud platforms have built niche technology capabilities and infrastructure
services that enables developers be innovative and agile – critical aspects to be competitive
and front runners in the Digital economy [9] [10] [11]. Accelerates ideation to productization cycle
• Niche technology services across AI/ML, Blockchain, IOT, Databases, Mobile etc. are available
for rapid prototyping & app development at low cost. Reliability, scalability, availability and
other non functional considerations are taken care by underlying infrastructure capabilities.
• Building cloud native apps with serverless technologies, assembly and configuration of niche
service capabilities and integrations across them to build complex enterprise apps will
continue further in 2019. Platform providers are focusing on development and management
tools of such applications and that will accelerate overall adoption pace.
• On AWS, there are 10,000+ customers using ML services. More machine learning happens on
AWS than anywhere else. Google is also leading efforts to simplify and democratize AI/ML for
the mainstream business use. With shortage of required skills in AI/ML field, businesses will
continue adopting trained ML models by these providers & use own data for custom solutions
• In re:Invent 2018, AWS announced it’s managed blockchain service to easily create and
manage scalable blockchain networks using Hyperledger Fabric and Ethereum. Google has
partnered with blockchain-focused firms Digital Asset & BlockApps to offer distributed ledger
technology frameworks on GCP. 2019 will see results of these initiatives.
• Microsoft Azure offers 100+ services and broadest set of hybrid capabilities and consistency
across on cloud and on premise applications. Tools like Visual Studio integrated in DevOps
ecosystem can improve developer productivity and help accelerate time to market.
• Enterprises will continue with multi cloud platform strategy and evaluate service capabilities
fitment in their solution context, workload technology alignment, de-management tools and
associated cost. 2019 will see enterprise solutions being built on such capabilities & services.
Management Tools Developer Tools
API Management Collaboration
Security Storage
Network & Content Robotics
Media Services Mobile
IOT Blockchain
Compute Database
Analytics ML

10. 4. “AI first” strategy will drive almost all enterprise IT initiatives
10
• Mature Enterprises will adopt “AI first” strategy for their enterprise IT initiatives similar to
Google[12] and Microsoft[13]. Artificial Narrow Intelligence (ANI) based apps focusing on
specific set of Data and use cases will set foundation for adoption of advance forms of AI.
• Cloud infrastructure from AWS[14], Google[15], Microsoft[16], etc. and AI optimized ML/DL Chips
and instruments from Intel[17], Nvidia[18] etc. will accelerate AI adoption at scale.
• Repetitive and routine jobs are already being automated through RPA initiatives. RPA and AI
together are bringing cognitive automation to the enterprises[19] which may replace and
create new set of jobs for the workforce.
• Conversational AI and voice enabled intelligent chatbots will continue transforming customer
experience. Personalized ‘Next Best Interactions’ will improve customer satisfactions.
• 2019 would also see simplification and standardization of ML/AI initiatives, frameworks and
technologies through consortiums and open source initiatives. OpenAI [20], AutoML[21], Open
Neural Network[22], Linux Foundation[23] etc. will see traction and improved adoption.
• End customer-facing AI applications will continue having ethical, bias, influence etc. related
issues[24]. Enterprises will continue bringing decisioning transparency & customer education.
• Availability of ML/AI talent will continue to be an issue across Data Scientists to developers.
• Solutions providers like Google[25] and Nvidia[26] will lead market of Industry specific AI bundle
for enterprises. Readymade solutions around customer experience, patient data
management, shopping experience personalization etc. will help accelerate time-to-market.
• AI has huge impact on mankind. We may see potential collaboration and partnerships
between research oriented countries and application oriented countries for evolution and
adoption of AI for betterment of human being. Similar to Finland’s AI education initiative[27],
countries will drive mass initiatives to educate their citizen on AI and technology in general.
Big Data
Ecosystem
Machine Learning / Deep Learning
ANI AGI ASI
Optimize
Automate
Recommend
Influence
Guide
…and more
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11. 5. Digital identity & biometrics with stepped up authentication models will
see increased adoption
11
• According to the new market research report by MarketsAndMarkets, the biometrics system
market is estimated to grow from USD 16.80 billion by 2018 to USD 41.80 billion by 2023 at a
CAGR of 19.99% between 2018 and 2023 [28].
• Biometrics will be adopted inside the enterprise as well as outside for authentication purpose.
Advancements in associated technologies will improve matching speed, performance, overall
security and user convenience[29].
• According to NIST’s report, facial recognition algorithms can identify matches with error rates
as low as 0.2% given good quality photos. 20 times better than what they found five years
ago[30]. 2019 and beyond will see updates & adoption of such advanced algorithms.
• Fast Identity Online (FIDO) [31] specifications around passwordless universal authentication,
2nd factor authentication, Web authentication (WebAuthn), and CTAP across mobile and web
environments will see wider adoption. Broad set of enterprises and product vendors will join
FIDO consortium in 2019 and collaborate on universal specifications.
• New versions of smartphones and web browsers will be equipped with biometrics and facial
recognition features[32].
• Critical use cases requiring high security will see multimodal biometrics with combination of
iris scan, voice, fingerprint & facial recognition in AND / OR formats. With geographic
coordinates, these authentication combinations can step up for location based security.
• As biometrics and facial recognition systems see wide adoption across financial institutions,
airports, home security, healthcare applications, etc., there would be continuous discussion
on transparency, regulatory control and ethical usage of such technologies [33].
• Research and innovation around applications of biometrics in regular life will see interesting
scenarios like Amazon Alexa to passively detect signs of illness and recommend remedies and
Walmart for connected shopping cart that can detect heart rate, palm temperature, etc. [34].
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Mobile Device Desktop / Laptop
Registration
Retina scan, voice, facial recognition, finger prints…
Passwordless Authentication
Second factor Authentication
Multi factor Authentication

12. 6. Blockchain - serious investment is expected to go up with fading doubts
12
• 2018 seen adoption of distributed ledger technologies in enterprise applications, except few
success stories, most of the experiments resulted in learnings. 2019 will see serious
considerations of distributed ledger / smart contracts based decentralized applications across
enterprises. Blockchain projects are expected to cross R&D stages to get into pilot and
production and start delivering promised benefits [35].
• Concrete use cases will get further scrutinized and funded for serious implementations.
Financial services, manufacturing, supply chain and energy & utility will be the key business
domains for blockchain adoption [36],[37] .
• As announced in October 2018, collaboration between Enterprise Ethereum Alliance and
Hyperledger will help in advancing global blockchain business ecosystem [38]. This relationship
will help evolution of these technologies as well as contribute to growth of both developer
communities.
• Cloud based platforms, solutions, services and developer productivity tools for writing
blockchain / decentralized applications will see adoption across enterprises. Examples include
Amazon managed blockchain, Amazon QLDB [39], Azure Blockchain Development Kit [40], and
IBM blockchain platform[41], SAP blockchain solutions [42] .
• Cryptocurrency will have its own challenges on acceptance & strict regulations from different
governments across geographies. Though there are hopes that cryptocurrency will get
accepted as general financial instrument, 2019 will be too early to see any results.
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Decentralized secure app ecosystem

13. 7. FinTech, InsurTech & RegTech will get highest priority on every CXOs charter
13
• Technology startups with lean operating structure will continue building niche technology
products around AI, blockchain, RPA, etc. to address very specific business needs. Their
struggle of engaging with legacy financial institutions to understand business processes and to
access data is expected to go down in 2019. Evaluation to onboarding cycles were longer so
far but can see acceleration in this process due to competitive pressures.
• According to CBInsights’ Global Fintech Report Q3 2018, VC backed Fintech companies raised
$5.64B across 375 deals globally. Aggregate Fintech unicorn valuation tops $115B. More than
competition, legacy financial institutions & Fintech will see value in collaboration[43] .
• In 2018, the top US 11 banks by assets participated in a total of 49 equity rounds to Fintech
startups mainly for a)high up-side returns and b)strategic partnerships. Banks have either
partnered or acquired fintech in automation, blockchain, personal finance, wealth
management, etc. [44]. This trend will continue in 2019 as banks offer alternate products or
integrate Fintech offerings in their product to bring value differentiation for their customers.
• InsurTech funding was on record breaking 2018 with $2.56B in investments YTD [45] across in
health, home, auto, life and B2B insurance startups. 2019 will be make-it-or-break-it year as
these startups will need to begin demonstrating Insurance business transformations[46] .
• Both financial institutions as well as regulatory bodies need to process huge data and analyze
reports in defined time periods. Big Data, ML, AI based analysis and reporting across
transaction monitoring, risk management, compliance, and regulatory reporting has become
very critical. New mandates and regulations around payments (PSD2) and data security
(GDPR) in Europe have increased overall complexity. 2019 will see evolution and adoption of
RegTech for improving accuracy and efficiency of their operations[47] [48].
• RegTech will help financial institutions improve their operating model which will result into
improved productivity and efficiency. RegTech will help mitigate compliance and operational
risks that will result into sustainability and business continuity [49].
Payments Personal Finance Lending
PFM Cryptocurrency KYC / AML
Risk Mgmt
Claims
Fraud
Reporting
Banks Insurance Regulators
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14. 8. IOT and smart sensors adoption will continue and see new use cases
14
• The global IoT market is expected to have a CAGR of nearly 27% from 2018 to 2024. Overall
the market is expected to grow to $6.5 trillion in 2024[50]. Factors driving the IoT market
includes declining cost of smart sensors and better cost efficiency in data processing.
• Smart Cities, Connected Industry, connected buildings and connected Health are the top IoT
adoption segments [51]. Other IoT adoption segments include smart supply chain, connected
car, smart retail and smart agriculture. This trend will continue in 2019 and beyond.
• Connected devices proliferation will continue at accelerated pace. According to CBInsights
estimate, by 2020 the average person will generate 1.5GB worth of data per day[52].
• Considering the connectivity challenges, data volume and speed of decisioning requirements,
adoption of edge computing with either specialized chips [53] or solutions like AWS
Greengrass[54], Google Cloud IoT Edge[55] & Microsoft Azure IoT Edge[56] will go up in 2019.
• Technavio report on industrial wearable market forecasted growth of over 10% through 2021.
The 3 trends are driving this growth – Digitization & automation, focus on workforce safety &
efficiency and, growing adoption of smart sensors [57]. This trend will continue beyond 2019.
• An intelligent enterprise that leverages ties between the physical & digital worlds that creates
better customer experience, drive operational efficiencies or enable new business models –
Tom Bianculli, CTO Zebra[58]. According to Zebra Technologies survey across 918 IT decision
makers from 9 countries, 49% are on the path of becoming “intelligent enterprises”[59] .
• End to end IoT solutions [60] across domains and solution accelerators[61] will continue to grow
in 2019 and beyond.
• Considering cyber security threats, nature of data collection and storage IoT devices and
systems carry out, there will be major push on security as well as regulatory and compliance
aspects. Worldwide IoT security spending from $1.5B in 2018 will go up to $3.1B in 2021[62].
Both vendors and users will have to be aware and mindful of nature of data collection and
storage.
Business apps : Data aggregation,
analysis & visualization
User Interfaces
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15. 9. App developers & Architects will continue unlearning and learning new
paradigms
15
• As the end user expectations and business demands are continuously growing, architects and
developers will have to continuously upgrade their skillset and master latest architecture
paradigm and technology stack to implement business solutions & address such needs.
• Full stack developers will be in demand who can understand tech stack, agile processes, test
methodologies and are familiar with domain constructs[63].
• Architects and developers will have to go through exercise of unlearning and learning to be
competitive in new age tech paradigm. Self-learning through online MOOCs providers like
Coursera, edX, Udacity and Udemy will continue to be most efficient sources. Universities
across the world are opening up their technical courses online as well.
• For practical hands-on experience across niche technologies, several online resources similar
to Linux Academy, QWIKLABS for cloud, Neptune.ml for machine learning will emerge.
• To be competitive in labor market, most of the organizations will focus on reskilling / upskilling
initiatives [64] for their resources with specific incentives associated with top performers.
• In addition to learning individual technology stack, Architects will have to think through and
master skills of blending multiple technologies together for addressing complex solution
needs. For example, implementing complex machine learning or blockchain projects on Cloud
platforms and integrating them with on premise legacy applications.
• As trend of FSD based agile app development is growing, along with technology skills,
developers will have to master skills of working in smaller, focused teams, own end-to-end
accountability of the product and need to be agile, collaborative, and performing in sprints.
• As Digital technologies especially ML/AI, Blockchain, IOT are going to be here for long time,
developers can define their individual learning roadmap and stick to it and achieve required
specialization. These technologies will see maturity improvements and standardization in
2019 / 20. 2019 will be the right time to latch on them and build career.
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?!?!?!?!?!?!?!?!?!?!?!?!?!?!?!?!?!?!?
!?!?!?!?!?!?!?!?!?!?!?!?!?!?!?!?!?!?!
Unlearn Learn Adopt
Align Practice Master
Data, ML, AI
Public Cloud
Blockchain
Cybersecurity Biometrics
FinTech / RegTech
Microservices / API
IOT / Sensors
PaaS / Containers
DevSecOps Languages / Frameworks
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16. 10. And top 3 programming languages developers must not ignore in 2019…
16
• Technology and technology frameworks are continuously evolving. Programming languages,
frameworks and libraries with capabilities specifically meant for ML/AI, Blockchain, advance
user experience, IOT etc. are emerging. Though there are several such programing languages
available, developers should not ignore JS (suitable frameworks), Python & Solidity in 2019.
• JavaScript based development of Web app, server backend, desktop and mobile apps
supports multi-platform development of complex apps. NodeJS, Vue, Angular and React will
see wide adoption in 2019.
• Sate of JavaScript survey across 20,000 developers across globe[65] found Vue.Js (front end
framework), GraphQL (Data Layer) and Next.JS (back-end framework) as prominent
frameworks. Developers wish to work on these frameworks in near future.
• Python is a general purpose language used across Data Science, ML/AI, Web apps, gaming,
etc. Web frameworks like Django, Flask and Data analysis, ML libraries like TensorFlow, Scikit-
learn and pandas are here to stay for long time. Also, IOT Device SDKs for cloud platforms like
AWS are available in Python. As developers see value of learning one programming language
and applying it across multiple popular areas, there will be surge in learning this language in
2019 and beyond.
• Blockchain apps with smart contracts written in Solidity language and running in Ethereum
VM will see wide adoption. Solidity is OO high-level language which was influenced by C++,
Python and JavaScript. Considering its statically typed nature, developers can catch errors
while they type and hence compared to other options [66] for blockchain development,
Solidity is a most popular option and continue to remain same in 2019.
Solidity
JavaScript
Python

17. 17
? So what…

18. Key Inferences…
18
USER EXPERIENCE
• Need to build / enhance
apps to interact with
systems & Users across
multi form factor devices
and formats – AR/VR, Voice
• Need to focus on engaging
digital experience driven
through insights (AI/ML)
• Growing demand of skills
around Design Thinking,
usability engineering and
experience design
• Need to upgrade UI/VUI/
VR/AR design skills.
• Need to master latest JS UI
frameworks
APP DEV PARADIGM
• Replicate cloud native arch/
tech paradigm across LOB
& enterprise consistently
• Green / brown field dev
through microservices, API,
DevOps, containers
(Docker, Kubernetes), PaaS,
& private / public Cloud
• Need to unlearn & learn
next gen FSD paradigm
• Master skills around MSA /
API, DevOps , Cloud and
modular, scalable product
engineering techniques
• Sharpen skills of working in
small teams in agile model
CLOUD
• Public Cloud platform
capabilities and service
offerings across AI/ML, IOT,
Blockchain are maturing
and can accelerate pilot
and serious adoption across
enterprise. Need to
provide serious attention.
• Build capabilities across
AWS / GCP / Azure service
offerings and accelerators
• Master patterns / anti-
patterns and integration
techniques across cloud
and off-cloud legacy
ecosystems
BLOCKCHAIN
• Need to follow success
stories to replicate & also
identify real use cases for
DLT / smart contracts based
business applications
• Can accelerate adoption
journey through cloud
based blockchain platforms
• Learn, master leading DLT
framework, smart contracts
constructs, programming
languages & Cloud service
offerings in this space
• Explore pilot / adoption of
blockchain + IoT, blockchain
+ digital identity, etc.
AI/ML
• Need to follow success
stories to replicate & also
identify real business
scenarios for AI/ML
• Acceleration through
proven platforms, models
& algorithms with business
context through own data
• Need to learn, master
AI/ML capabilities from the
cloud platforms
• Explore opportunities of AI
application across business
domains.
• Learn, master skills around
AI + RPA, AI + Voice, etc.
ENTERPRISESDEVELOPERS
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19. Key Inferences…
19
Biometrics
• Follow success stories &
identify real use cases for
biometrics adoption
• Follow FIDO consortium
initiatives & specifications
• Educate end users on
biometrics as appropriate
• App design for biometrics
• Understand FIDO UAF/U2F
specifications
• Explore FIDO compliant
products & implementation
/ integration opportunities
• Track / follow biometric
evolution – especially facial
recognition techniques
IOT / SMART SENSORS
• Follow success stories &
identify real use cases in
the business context
• Explore cloud IoT platform
capabilities for for overall
acceleration purpose
• Review, follow IoT security
initiatives & products
• Learn, master Cloud IoT
platforms & services
• Focus on Edge computing &
major vendor service
offerings
• Track trends and
technology evolution
including smart sensors /
5G connectivity etc.
FINTECH/INSURETECH
• Track Fintech / InsurTech /
RegTech in business
context and explore
opportunities for alliances,
investments or acquisitions
• Collaboration with FinTech
/ InsurTech is the key to
success than competition
• Follow Fintech / InsurTech /
RegTech momentum
• Explore opportunities for
evaluating niche products /
offerings in blockchain,
AI/ML, IoT areas
• Be active proponent /
advocate to onboard
genuine offerings
LANGUAGES
• As programming paradigm
is changing, make internal
developers aware of what
is coming at the enterprise
level, mentor them, groom
them and provide them
opportunities to learn and
upskill themselves
• Cross-skill / Up-skill is
absolutely necessary
• Focus on programming
paradigm / languages like
JavaScript, Python &
Solidity which are popular
and powerful in next gen
app development space
UNLEARN-&-LEARN
• Create ecosystem of
continuous learning with
rewards & recognition to
motivate masses
• Make developers aware of
next-gen app dev paradigm
and instill need to up-skill
technology know-how
• With changing paradigm,
developers must upgrade
skills with focus on what is
popular & in demand
• Self learning through
MOOCs, Product vendor
educations & technology
meetups is essential
ENTERPRISESDEVELOPERS
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20. Reference [1-of-3]
20
1 Crossing the chasm https://www.youtube.com/watch?v=A2LRFhqi0zw
2 Why Digital strategies fail https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/why-digital-strategies-faiL
3 JJ Kercher – A roadmap for maturing design in the Enterprise https://www.youtube.com/watch?v=mbLSD04kZRM&index=11&list=PLS-xE0iEIwRmJLe_oLAAWq_aWioUtIsaS&t=993s
4 Artificial Intelligence (AI) Chatbot trends in 2019 https://www.youtube.com/watch?v=NrNTlqMzjj8
5 Adobe Analytics Predicts How Voice Will Change in 2019 https://theblog.adobe.com/adobe-analytics-predicts-how-voice-will-change-in-2019/
6 IBM Enterprise outlook on Cloud native development https://www.ibm.com/cloud/cloud-native-research/
7 CNCF survey : Use of Cloud native Technologies https://www.cncf.io/blog/2018/08/29/cncf-survey-use-of-cloud-native-technologies-in-production-has-grown-over-200-percent/
8 Collabnet Blog : Agile & DevOps Trends https://blog.versionone.com/12th-annual-state-of-agile-report/
9 AWS Cloud solutions https://aws.amazon.com/solutions/
10 Google Cloud solutions https://cloud.google.com/solutions/
11 Azure Cloud solutions https://azure.microsoft.com/en-us/solutions/
12 Google’s AI-First strategy https://www.youtube.com/watch?v=5WRJYEA-mwY
13 Where to use AI and why? https://info.microsoft.com/ww-landing-gartner-report-where-to-use-ai-and-why-eBook.html?lcid=en-us
14 AWS : What is AI. Machine learning & deep learning https://aws.amazon.com/machine-learning/what-is-ai/
15 Google : Cloud AI products https://cloud.google.com/products/ai/
16 Azure : AI products https://azure.microsoft.com/en-us/free/ai/
17 Intel AI products family https://ai.intel.com/
18 Nvidia AI products family https://www.nvidia.com/en-us/deep-learning-ai/
19 RPA & AI – The new intelligent digital workforce https://www.kofax.com/Blog/2018/september/rpa-and-ai-the-new-intelligent-digital-workforce
20 OpenAI research and systems ecosystem https://openai.com/
21 AutoML – Making ML available to non-ML experts https://www.ml4aad.org/automl/
22 Open neural network exchange format https://onnx.ai/

21. Reference [2-of-3]
21
23 Linux Foundation Deep Learning https://lfdl.io/
24 Bias in AI increasingly recognized, progress being made https://aitrends.com/ethics-and-social-issues/bias-in-ai-increasingly-recognized-progress-being-made/
25 Google AI solutions https://cloud.google.com/solutions/ai/
26 Nvidia deep learning / AI solutions https://www.nvidia.com/en-us/deep-learning-ai/industries/
27 AI free online course https://www.elementsofai.com/
28 Markets&Markets : Biometric Systems Market forecast https://www.marketsandmarkets.com/PressReleases/biometric-technologies.asp
29 Bringing biometrics to the door and across the enterprise https://www.biometricupdate.com/201811/bringing-biometrics-to-the-door-and-across-the-enterprise
30 Facial recognition 20 times more accurate… https://www.biometricupdate.com/201812/facial-recognition-20-times-more-accurate-with-advances-in-convolutional-neural-networks-nist-finds
31 Fast Identity Online Alliance https://fidoalliance.org/
32 New version of chrome supports fingerprints auth… https://findbiometrics.com/new-version-of-chrome-supports-fingerprint-authentication-for-websites/
33 AI / Facial recognition & ethical discussions https://findbiometrics.com/nec-welcomes-ethical-regulatory-discussions-facial-recognition-ceo-512182/
34 Biometrics – innovations & patents overview https://www.mobihealthnews.com/content/walmart-amazon-patents-could-take-biometric-monitoring-new-level
35 PWC : Blockchain is here. What’s your next move? https://www.pwc.com/gx/en/issues/blockchain/blockchain-in-business.html
36 IBM : Blockchain use cases https://www.ibm.com/blockchain/use-cases/
37 Blockchain for 2018 & beyond https://www.linkedin.com/pulse/blockchain-2018-beyond-growing-list-use-cases-filipowski-1/?trackingId=R6J17arzemU1VIY2vtVhIQ%3D%3D
38 EEA & Hyperledger alliance https://www.hyperledger.org/announcements/2018/10/01/enterprise-ethereum-alliance-and-hyperledger-to-advance-the-global-blockchain-business-ecosystem
39 AWS : Blockchain https://aws.amazon.com/blockchain/
40 Azure Blockchain Development Kit https://azure.microsoft.com/en-us/blog/introducing-the-azure-blockchain-development-kit/
41 IBM Blockchain Platform https://www.ibm.com/blockchain/platform
42 SAP Blockchain solutions https://www.sap.com/products/leonardo/blockchain.html
43 CBInsights : Global Fintech Report Q3 2018 https://www.cbinsights.com/research/report/fintech-trends-q3-2018/
44 CBInsights : Where top US Banks are betting on Fintech https://www.cbinsights.com/research/fintech-investments-top-us-banks/

22. Reference [3-of-3]
22
45 InsurTech Landscape https://www.cbinsights.com/research/report/insurance-tech-landscape/
46 InsurTech trends 2019 https://tearsheet.co/insurtech/the-49-biggest-trends-in-insurance-and-insurtech-for-2019-according-to-experts/
47 Deloitte : RegTech Universe https://www2.deloitte.com/lu/en/pages/technology/articles/regtech-companies-compliance.html
48 Protoviti : RegTech Roundup https://www.protiviti.com/US-en/defining-regtech
49 Capgemini : Top 10 trends in Capital Markets : 2019 https://www.capgemini.com/wp-content/uploads/2018/11/Top-10-Trends-in-Capital-Markets-2019.pdf
50 Energias Market Research: Global IoT Market Report https://globenewswire.com/news-release/2018/04/17/1479964/0/en/Global-Internet-of-Things-IoT-Market-to-witness-a-CAGR-of-26-6-during-2018-to-2024-Energias-Market-Research-Pvt-Ltd.html
51 Forbes : 10 charts that will challenge your perspective on… https://www.forbes.com/sites/louiscolumbus/2018/06/06/10-charts-that-will-challenge-your-perspective-of-iots-growth/#3efb23d03ecc
52 CBInsights: Edge Computing https://www.cbinsights.com/research/what-is-edge-computing/
53 Intel : IoT products https://www.intel.com/content/www/us/en/internet-of-things/iot-analytics-and-manageability.html
54 AWS IoT Greengrass https://aws.amazon.com/greengrass/
55 Google : IoT products https://cloud.google.com/products/#internet-of-things
56 Azure : IoT Edge https://azure.microsoft.com/en-us/services/iot-edge/
57 IEEE : Industry IoT growth trends https://innovationatwork.ieee.org/industry-iot-growth-trends/
58 Zebra : POV on Intelligent Enterprise https://www.businesswire.com/news/home/20171101005117/en/Zebra-Study-50-Percent-Enterprises-Achieved-%E2%80%9CIntelligence%E2%80%9D
59 The Intelligent Enterprise Index https://www.zebra.com/content/dam/zebra_new_ia/en-us/campaigns/brand-campaign/harvard-symposium/how-intelligent-enterprise-survey-index-en-us.pdf
60 Intel : IoT solutions https://www.intel.com/content/www/us/en/internet-of-things/market-ready-solutions/market-ready-solutions.html
61 Azure IoT solution accelerators https://azure.microsoft.com/en-us/features/iot-accelerators/
62 IoT Security spending trends https://www.i-scoop.eu/internet-of-things-guide/iot-security-spending-2018-2021/
63 Full Stack Developer – required skills in 2019 https://www.quora.com/What-should-a-real-full-stack-web-developer-know-in-2019
64 Tech reskilling drive https://www.weforum.org/press/2018/01/1-million-workers-targeted-in-tech-reskilling-drive/
65 State of JavaScript survey 2018 https://2018.stateofjs.com/introduction/
66 Best Blockchain programming language https://www.ubuntupit.com/best-blockchain-programming-language-top-15-reviewed-for-blockchain-programmer/

23. 23
Thank You!
Swarraj Kulkarni
swarraj@gmail.com
linkedIn.com/in/swarraj
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