Intelligent adoption of artificial intelligence
AI
has the potential to disrupt the core of business processes. However, blind
adoption of technology and hype-based purchase may not lead to the desired
results
Artificial
intelligence (AI) is one of the most talked about technologies in recent times.
It is capable of increasing enterprise revenue through identifying, analysing
and, most importantly, acting on the insights from underlying data. The
pertinent question is, “Should we wait for AI to evolve fully and then apply it
or should we look at specific applications to solve business challenges?”
Range
of AI—Human assistant to human replacement
The
combination of parallel processing power, massive data sets, advanced
algorithms and machine learning capabilities are spawning varied versions of AI
systems.
Today,
AI capabilities vary from specific/narrow to super, all-encompassing AI.
Narrow,
or specific AI, is an intelligent assistant that can aid humans in making
complex decisions and enhance their cognitive powers by processing vast amounts
of data. It can conceptualize and correlate data, recognize the patterns and
deliver intelligent output.
For
instance, soft AI can be used to detect frauds in various sectors such as
banks.
A
large sample of fraudulent transactions is fed into the AI system, which is
trained to look for signs that separate fake transactions from genuine ones.
Another
example of soft AI is the voice assistant that can understand voice inputs,
analyse data about the users from a variety of sources (social media,
smartwatches, etc.) to better understand their behaviour and deliver results
tailored to users’ preferences.
Super,
or strong AI, aims to make decisions on its own without any external support.
These
machines can think, learn, decide and converse like humans. Hence, they have
the ability to replace humans altogether.
However,
super AI systems are yet to achieve breakthrough improvisation to fully
comprehend human mind-maps and replicate human intelligence.
How
is AI different from RPA and cognitive?
Though
enterprises are increasingly understanding the benefits of AI, there still
exists misperception around similar technologies—AI, robotic process automation
(RPA) and cognitive.
AI
is described as the decision-taking capability based on simulation of human
intelligence processes by machines. These machines “can act” as human.
On
the other hand, cognitive computing helps humans in fully or partially
delivering judgement-based processes and assists in their decision-making.
These systems deal with unstructured inputs, and “can think” as humans.
The
third type, referred to as RPA, can automate rule-based tasks and “can do” what
humans can. Such systems lack self-learning capability and are effectively
dumb: they just perform exactly as programmed.
AI-use
cases in business
As
customers are becoming increasingly demanding, AI offers assistance on key
requirements of evolving business:
• People-centric:
The AI systems enable the enterprises to shift to a people-centric approach
from being process-centric. The decisions are made based on unstructured
real-time data rather than pre-defined processes. For instance, ride-sharing
companies predict fleet demand based on factors such as weather forecasts, time
of the day and historical customer behaviour.
• Ease
of use: AI enhances customer experience with offered convenience and
assistance. For example, enterprises are using “customer digital assistants”
that can recognize customers by face and voice to have relevant conversations,
and provide tailored choices to help them make purchasing decisions.
• Self-adaptive:
AI has the capability to self-evolve, make connections between data,
improve on past decisions and get smarter. For instance, machine learning-based
intelligence enables an enterprise to improve sales performance by accurately
predicting cross-selling and up-selling opportunities.
AI
implementation strategy for enterprises
AI
has the potential to disrupt the core of business processes. However, blind
adoption of technology and hype-based purchase may not lead to the desired
results. Enterprises can ride the wave of success with efficacious adoption of
AI technology:
• Getting
familiar with the concept: Rather than adopt the technology in haste,
enterprises should first educate themselves on the basic concepts and
capabilities of AI. The better a company understands what narrow/soft AI does,
the more likely is its successful adoption.
• Identifying
the problem to which AI is a solution: Enterprises should identify specific
use cases in which AI could solve business problems and help them achieve
specific project goals. They should further narrow down the possible AI
implementations by assessing potential business and financial values.
• Bridging
the talent gap: AI requires talent pool with a strong understanding of
advanced programming, domain knowledge and business context. Enterprises should
bring these skills together instead of waiting for one person to bring all the
dimensions.
The
importance of AI is well understood. However, its implementation remains
limited.
It
is imperative for firms to start applying AI for solving narrow-scope problems
before expecting it to disrupt the core of the business.
AI
can be employed for everything from managing targeted advertisements to
optimizing logistics to tracking assets to understanding the customers’ social
behaviour. The trick is to get started on the right note.
Source | Mint – The Wall Street Journal | 30 March
2017
Regards
Pralhad
Jadhav
Senior
Manager @ Knowledge Repository
Khaitan & Co
Upcoming Event | MANLIBNET 17th Annual
International Conference on 15-16 September 2017 at Jaipuria, Noida, India
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