9 Digital Transformation Trends for 2023

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9 DIGITAL TRANSFORMATION TRENDS FOR 2023
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1. 5G and IoT
5G is the fifth generation technology for mobile
networks. 5Gs primary characteristics include
multi-peak data speeds, low latency, improved
user experience, better connectivity and
availability, and improved network bandwidth.
Some of the use cases of 5G in the IoT domain
include
1. Connected Automobiles 5Gs low latency and
high bandwidth will enable vehicles to store and
initiate bi-directional communication. 2.
Shipping and Logistics Easy and accurate
tracking of shipped items. This will allow
updating precise delivery timelines, which, in
turn, will improve customer experience 3. Remote
Healthcare 5G connectivity will also enable
seamless remote patient monitoring. Also, health
experts can provide assistance at any time and
from anywhere irrespective of their location.
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2. Zero-Trust Security
With many organizations adopting the remote-first
culture, the risk of cyberattacks has increased.
Thus it becomes essential to introduce zero-trust
security to prove resilient. Organizations are
already planning/implementing migration to a
cloud-based, zero-trust security model. The new
security solution will help establish trust,
authority, brand reputation, and initiate safe
B2B communications.
Zero-trust security aids in securing
applications, data, identity, endpoints,
networks, and even infrastructure.
The three primary principles of zero-trust
security include
Require secure and authenticated access to all
resources.
Adopt the least privilege model and Enforce Access
Inspect and Log all activities using data
security analytics
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3. Software 2.0
Software 2.0 is a technology that automatically
creates source code from the requirements
document. This can be done through Deep Learning
(DL) that helps build neural networks for
automating code drafting.
Software 2.0 is still at the market entry stage
and to implement it, businesses will have to gain
expertise with DataOps (Data Operations) and
MLOps (Machine Learning Operations).
DataOps is a process followed for data teams to
improve data quality and the efficiency and
accuracy of data analytics activities. On the
other hand, MLOps is a part of DataOps and helps
in enhancing machine learning operations,
introducing automation, and increasing emphasis
on understanding business requirements.
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4. Data Fabric
What is Data Fabric?
Consider a self-driving car and two-related
scenarios The driver manually drives while the
automated features are not put into use
The driver loses focus and the automated features
get activated and make course corrections
whenever required
This is similar to how data fabric works. The
data fabrics help make suggestions that make data
teams more productive (whenever required). When
the data experts are satisfied with automated
course corrections, the lever can be handed over
to the data fabrics entirely. This helps the data
teams focus on their core activities while the
monotonous tasks are managed by data fabrics.
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5. Hyperautomation
Hyper Automation aims to automate business and
IT processes to a large extent. Whether it is RPA
(Robotic Process Automation), low-code/no-code
adoption, or AI and machine learning businesses
plan to upscale investments in automation.
Some of the hyper automation-oriented initiatives
include a. RPA (Robotic Process Automation)
Robotic Process Automation handles repetitive
tasks at work using software robots. RPA helps
increase speed to market, reduces expenditure,
and increases business operations scalability.
b. Low-Code Platforms
Low-Code platforms offer drag and drop features
to build software. There is minimum coding
knowledge required, which makes it an innovative
platform for non-tech folks.
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6. Total Experience
Total experience (TX) combines user experience
(UX), customer experience (CX), and employee
experience (EX) to enhance brand impression at a
holistic level. Top Two Reasons for Pursuing
Digital Initiatives enhance customer experience
(58)
improve employee productivity (57)
One may find various CRM (Customer Relationship
Management) or CXM (Customer Experience
Management) applications. With the evolution of
TX, you will notice the emergence of
disruptive applications that solve the pain
points of customers and employees alike.
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7. Everything as a Service (XaaS)
Everything-as-a-service or Anything-as-a-Service
is the latest digital transformation trend that
promotes the as-a-service model and delivers
anything to the customers. XaaS goes beyond the
traditional cloud service model, i.e., SaaS,
PaaS, and IaaS, and includes more services such
as
XaaS also paves the way for Servitization,
i.e., offering a
combination of products and services in one
package. A simplified example of servitization is
Amazons Alexa where AI-driven services are
offered along with portable hardware products.
Storage as a Service (STaaS) Containers as a
Service (CaaS) Function as a Service
(FaaS) Security as a Service (SECaaS) Unified
Communication as a Service (UCaaS) Video as a
Service (VaaS)
The latest real-world example of XaaS comes in
the form of a partnership between Hewlett Packard
Enterprise (HPE) and Veeam. Both HPE and Veeam
have proved expertise in safeguarding data,
ensuring data availability, and
maintaining business continuity and resilience.
With this partnership in place, Veeam and HPE aim
to safeguard your data irrespective of where you
position it (on or off-premise). The data
protection services are offered through the
as-a-service model.
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8. Generative AI
Generative AI is a branch of artificial
intelligence that uses existing content (images,
texts, audio, video) to create similar yet
original content.
The most popular example of Generative AI are
Face apps where the user provides their image as
input, and the app shows how they would look
across different age groups.
There are three different types of techniques
that we can leverage for implementing Generative
AI, which include
GAN (Generative Adversarial Network) Comprises
of two neural networks, i.e., generative network
and discriminator network Transformers Include
GPT3, LaMDA, and Wu-Dao Variational Autoencoders
is a type of artificial neural network architectur
e
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9. AR Cloud
AR Cloud (Augmented Reality Cloud) is a digital
3D copy of the real-world environment created
using its spatial properties.
We also call it the digital twin of any
real-world environment and also enables sharing
the experience with multiple users in real-time.
Though the success of AR Cloud will depend on the
maturity of 5G networks, businesses such as
Facebook, Apple, Google, Amazon, Visualix, and
Scape technologies are leveling up investments in
the technology.
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Conclusion
No matter what technology you plan on picking,
the idea is to innovate and introduce a
unique selling point (USP) that will contribute
towards quantifying ROIs.
Digital Transformation is the adoption of digital
technology by an organization that will, in turn,
helps trigger disruption and drive revenues.
Every year, promising digital transformation
trends emerge that hold the potential to
accelerate business growth.
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