
DagangNetPOST recently spoke to Puan Nuraslina Zainal Abidin in her vibrantly designed office as she explained in detail what artificial intelligence is and how the technology can permeate into our work and home lives.
What is artificial intelligence in brief?
Artificial intelligence ("AI") is the ability of a machine to perform cognitive functions such as perceiving, reasoning, learning, interacting with the environment, and problem solving.
In short, AI is a collection of technologies that allow machines to perform human-like tasks.
Who are potential users or vertical markets where AI can be applied?
Actually, we encounter a form of AI every day as the technology could affect our decisions and our lifestyles.
The technology is applicable across various functions and vertical markets. It is a multi-trillion-dollar industry, and as we continue to unlock the secrets of things like natural language processing and neural networks, AI becomes even more appealing.
Unfortunately, its adoption is rather slow as organisations have not mastered the art to embrace AI yet. This due to challenges such as lack of access to AI talents and readiness of organizations to incorporate AI as a business strategy.
What is the level of adoption of AI among organisations?
As Malaysia transitions to a digital and data-driven economy, we expect to see a greater level of AI adoption especially in the development of smart cities, and followed by various industry sectors including telecommunications, financial services, and healthcare. According to a study by IDC, 34 per cent of organisations in Malaysia have plans to adopt AI within the next two years, the second highest rate among Asia Pacific countries.
There are challenges across sectors for those that are embarking on their data-to-insights journey. Example, organisations in the financial services space face more challenges in data collation and model building, while public sector organisations are hindered by data readiness issues.
How should an organisation best approach AI?
As transformation consultants, we can assist customers to first discover how the different spectrums of AI solutions can benefit their organization. This is normally conducted jointly with the customer with our AI Discovery Workshop approach. The session will allow us to identify solutions that can be implemented to solve their industry specific business problems. We assist customers to find the critical processes within the organisation that requires improvement or re-engineering or redesigning to deliver better customer experience and improved bottomline.
We would recommend a three-step process to guide our customers in their AI experience journey:
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Step 1 : Select a Decision
We engage internal and external stakeholders to understand what matters - speed, accuracy, quality. Determine what business decision that would be useful to augment or automate with AI that will impact customer experience.
Good candidates of AI implementation have these two qualities:
High Frequency
- The decision is made at least 300 times per year across all employees. Higher frequency is even better, because it will mean more data to feed the algorithms and greater opportunity to save time and improve decision making.
Multiple Factors
- There are least a few inputs that a person would use to determine the best decision each time. The more inputs, the better, since machines are much better at dealing with dozens or more variables than people are.
1. Manager Approvals
Determine if an expense or a discount on a sales opportunity should be automatically approved.
2. Routing Emails / Tickets
Categorise, prioritise and route emails or support tickets based on the content of the inquiry, the language of the text, the sender and other factors.
3. Forecasting
Predict the likelihood of a sales opportunity to close, the risk of a customer to cancel, or the estimated completion time for a project.
4. Auto-Responses
Automatically completing RFPs and RFIs based on a library of past responses or responding to a customer question with the likely best answer.
5. Flagging Anomalies
Sift through several records to identify the small set of outliers that need to be reviewed or analysed.
AI Recommendation
Enable AI to analyse the data and provide a recommendation to a person. This allows for the subject matter experts to observe the AI, gain trust that it's making sound decisions, and also save some time as they are making those decisions.
Assisted AI Decision
Set parameters for when it's appropriate for the AI to make a decision and when that decision should be made by a person. These parameters could include the confidence of the AI in the decision, as well as the stakes or risk for a decision based on the factors.
Automated Augmented AI Decision
For some decisions, an AI will learn to become more accurate than people, or at least accurate enough that the time savings for people is worth having the AI fully automate the decision.
Step 2 - Gather Data
Where the data resides does not matter so much, but it will need to be digitized and not sitting in stacks of paper. It also needs to be labelled in a structured way namely either fields in a system or database, or a spreadsheet with rows and columns. If you don't have enough labelled data yet, the best approach will be to start the discipline of gathering the factors and decisions in a structured way, so that you can use it to feed the AI platform in the near future.
Step 3 - Select an AI Platform
All organisations will need a platform to bring AI to their decision-making process. We guide our customers in their selection process by considering these factors:
Required AI Capabilities
We provide options to our customers on their decision of possible automation or augmentation. Bringing different ready-made solutions or Bespoke solutions will depend on what is the spending capability of our customers. These could include machine learning, natural language processing, optical character recognition, fuzzy matching, sentiment analysis, image recognition, and more.
Data Readiness & Integration
Our advice is for this process to be as automated as possible from ingesting historical and future data to recording decisions and initiating actions in other systems. We provide clients different options to connect to the systems, spreadsheets, or databases that will be involved in either supplying data or receiving the outcomes of the decisions.
Workflow & Tasks
Organisations will want to be able to control whether this is an AI recommendation or assisted AI decision, and you should be able to assign tasks to people to be able to take action when the AI decision-making is not fully automated.
Flexibility
Change is inevitable. We provide the clients options to be able to update factors for the decision, change the source or output system, or modify the workflow on their own as clients may want to be able to make all these changes without requiring an engineer or data scientist every time. Alternatively, we also provide a support model which includes maintaining the changes as per business operational needs.
You make it sound easy, but I am pretty sure many organisations get a headache (and heartache) in their attempt on AI implementation
We feel that our customers need someone who can guide them through the complexity of AI with transparency. Once we've discussed business problems that need remedies, we guide our customers through the critical steps of adopting AI into their business.
Call us.