The enterprise of the future will increasingly depend on a wide range of rigorous artificial intelligence systems, algorithms and techniques to facilitate its operation at all levels of e-commerce management.
As described in The Adaptable Enterprise blog, major decisions incorporating sophisticated levels of intelligent problem-solving will be increasingly applied autonomously within real time constraints to achieve the level of adaptability required to survive in an ever changing and uncertain global environment.
In addition web services will draw on the advances already made by the semantic web combined with the intelligent web 4.0.
A number of artificial techniques and algorithms are rapidly reaching maturity and will be an essential component of Intelligent Enterprise Architecture of the future.
Current techniques include-
Genetic algorithms- achieve solution discovery and optimisation modelled on the evolutionary natural selection process- based on the genetic operators of cross over, replication and mutation and measured against a 'fitness function'.
This technique is widely applied to solve complex design and optimisation problems.
Bayesian networks- graphical models representing multivariate probability networks- providing inference and learning based on cumulative evidence- widely used in medical diagnosis
Fuzzy Logic- based on natural non-binary methods of decision-making- assigns a
Swarm Intelligence- combines multiple cooperating components to achieve group intelligent behaviour.
Neural networks- pattern discrimination techniques modelled on neuron connection.Allows information inputs to be weighted and an activation threshold established.
Expert Systems- rule based inference techniques targeted at specific problem areas.
Intelligent Agents- designed to be adaptive to the web's dynamic environment- an agent is designed to perform a goal and learn by experience- can also act collaboratively in groups achieving higher levels of intelligence and capable of making increasingly complex decisions autonomously.
The above techniques will continue to be enhanced and packaged in different combinations to provide immensely powerful problem solving capability over time. The technology is slowly being applied discretely within business intelligence, data mining and planning functions of enterprise systems.
However AI is yet to realise its full potential within the enterprise by being applied to decision-making in a targeted autonomous fashion.
When this happens over the next decade, the quality of decision-making and concommitant reduction in operational and management risk is likely to be significantly improved.