has added a new dimension to enterprise applications,
quickly adapt to changing business requirements as well
as direction of market movement and actions of competitors.
By Dr Kaustubh Chokshi*,
CEO of UK-based Intelligent Business Systems.
marked 50 years since the term "Artificial Intelligence"
was coined. Over this period of half a century, AI has
captured our imagination of as we fantasised about the
day when machines would routinely carry out normal conversations
with humans and do all our work. However, it''s no secret
that on this count AI has so far only flattered to deceive.
the AI story, in actuality, has turned out to be quite
different from what was originally envisaged by the pioneers
of the technology. While the quest to replicate general
human intelligence continues, AI researchers have meanwhile
concentrated on producing software with specific expertise
that in many cases far outstrips human intelligence in
the niche functionality it is designed for. As a result
there are myriad AI applications all around us that we
hardly even notice, and the technology has become rather
pervasive in today''s world.
In previous articles on domain-b, I attempted
to explain some of the philosophy and concepts that go
into AI-based software, and briefly described artificial
neural networks-the basic building blocks forming the
architecture for software that learns from experience
and gets better the more it is used.
has to understand that the massive amounts of data being
generated today cannot possibly be analysed effectively
enough either by humans or traditional software, if one
wishes to derive all the knowledge inherent in that data
or ascertain the intrinsic hidden patterns. It is here
that AI is playing a big role, whether in biotechnology
or in banking.
technologies are diverse, and find application in a very
wide range of fields. In this series, I restricted discussion
to business applications, but AI has proved useful in
other areas as well. To take just a couple of examples,
today, vision-recognition systems alert security guards
to potential threat or danger situations in buildings,
car parks, supermarkets and even beaches.
software can actually remotely pilot airplanes, and in
the near future, most cars would be equipped with AI-based
"auto drivers". Of course, even today most modern
cars are equipped with significant levels of AI to optimise
fuel efficiency and engine longevity.
While I discussed specific business applications in my
previous articles-such as forecasting tourism demand,
anti money laundering, customer profiling, and loyalty
systems-I would like to wrap up this brief series by giving
you a broad perspective on the inroads made by AI technology
into enterprise-level applications. Cutting-edge AI techniques
are being used to develop enterprise software that can
dynamically adapt to rapidly changing business environments,
while simultaneously providing high levels of decision
support and trends forecasting for enterprise managers
to act on.
software garners knowledge from the data generated within
the organisation, as well as from expert opinion and external
data sources, and learns as it goes along. This has great
relevance, because businesses operate in a non-linear
environment, characterised by hard-to-predict (but non-random)
cause and effect relationships. Tiny changes in conditions
could lead to widely varying outcomes, and mere logic-based
software would be hard-pressed to provide meaningful decision
support in such scenarios.
On the other hand, decision management using AI enables
automated improvement of operational and tactical decisions
across the enterprise, with higher levels of precision,
consistency and agility. All this while reducing the time
taken to decide (decision latency), and the cost involved
in making each decision.
can be applied to virtually any business area that involves
high-volume, operational decisions, or the use of analytics
and business rules to improve decision strategies. Many
of these activities fall under the purview of supply chain
management, customer relationship management, data mining
and business intelligence. In all of these enterprise
level applications, AI can play a significant role in
providing the enterprise with that elusive competitive
supply chain management is generally agent-oriented. It
is composed of a set of intelligent software agents, each
responsible for one or more activities in the supply chain
and each interacting with other agents in the planning
and execution of their responsibilities. So, for example,
one could have a "logistics agent" responsible
for coordinating the factories, suppliers, and distribution
centres to achieve on-time delivery, cost minimisation,
inventory optimisation, etc. This agent would provide
inputs to the "transportation agent", responsible
for the assignment and scheduling of transportation resources
to optimise movements of goods.
problem-solving abilities of the intelligent software
agents take real world uncertainties and constraints into
account and dynamically cooperate among themselves to
optimise the chain based on the set goals. Agents can
develop plans that satisfy internal constraints, as well
as those of other agents, in a coordinated manner. Constraints
that cannot be satisfied are modified by the subset of
agents directly involved, in a process of negotiation
that has optimisation of the overall supply chain as the
ultimate goal. AI plays a key role not only by making
the best use of capacities in the system (asset utilisation),
but also by ensuring that all forecast demands are met.
aim of AI-based customer relationship management is to
accurately map consumer wants and desires to product offers
and promotions, in order to maximise satisfaction and
increase yields. AI can play a significant role in this
exercise of customer profiling and devising the perfect
product-customer fit. This is because AI-based software
takes into consideration actual transaction data to detect
hidden patterns in consumer behaviour. Add to this expert
opinion and relevant factors from the external environment
and you have a system that provides for razor-sharp precision
marketing. Once cross-selling, up-selling and general
promotional offers are no longer based on clumsy or brute-force
marketing, customer indifference and even irritation soon
give way to satisfaction.
Data Mining can be looked at as one stage in the development
of an AI-based system. In essence, data mining applies
sophisticated mathematical techniques to search for useful
patterns in large databases. The use of AI techniques
such as neural networks and Bayesian inferencing augments
the process significantly. AI techniques can be used to
take data mining a step further and utilise the established
data patterns to make forward-looking predictions or dynamically
generated multiple categorisations of customers by evaluating
multiple data patterns.
true worth of AI technology is most evident in Business
Intelligence applications. With AI, BI goes beyond decision
support and fixed rule-based analysis to offer true decision
automation. Historical information on company operations
and customer activity can be used to channel decisions
in the right direction. The AI software sets or helps
set the criteria to make predictions from existing sets
of data and generates scoring algorithms for weighting
different data characteristics. It is only in AI-based
software that predictive analytics-the ability to predict
likely future results and scenarios from historical data-can
be accurate, meaningful and beneficial.
Intelligence capabilities have added a new dimension to
enterprise applications, helping organisations quickly
adapt and respond to changing business scenarios, as well
as direction of market movement and actions of competitors.
This represents a new and emerging
paradigm in software architecture and offers enterprises
that take advantage of it greater agility in everything
they do. AI has well and truly arrived in the enterprise.
The big question: Has it arrived in your enterprise? Or
only at your competitor''s?
Dr Kaustubh Chokshi is CEO of Intelligent Business Systems
(IBS), a UK-based AI Enterprise Solutions company, which
has recently expanded into India. Dr Chokshi has a PhD
in Artificial Intelligence from the University of Sunderland,