Organisations are moving beyond digitalisation to a focus on building market differentiation. It is widely acknowledged that customer-centric strategies lead to better business outcomes, including increased customer satisfaction, loyalty, competitiveness, growth, and profitability.

AI is the key enabler driving personalisation at scale. It has also become key to improving employee productivity, empowering them to focus on high-value tasks and deepening customer engagements.

Over the last month – at the Salesforce World Tour and over multiple analyst briefings – Salesforce has showcased their desire to solve customer challenges using AI innovations. They have announced a range of new AI innovations across Data Cloud, their integrated CRM platform. ​

It is not hyperbole to state that AI is on the cusp of having significant implications on society, business, economies, governments, individuals, cultures, politics, the arts, manufacturing, customer experience… I think you get the idea! We cannot understate the impact that AI will have on society. In times gone by, businesses tested ideas, new products, or services with small customer segments before they went live. But with AI we are all part of this experiment on the impacts of AI on society – its benefits, use cases, weaknesses, and threats. 

What seemed preposterous just six months ago is not only possible but EASY! Do you want a virtual version of yourself, a friend, your CEO, or your deceased family member? Sure – just feed the data. Will succession planning be more about recording all conversations and interactions with an executive so their avatar can make the decisions when they leave? Why not? How about you turn the thousands of hours of recorded customer conversations with your contact centre team into a virtual contact centre team? Your head of product can present in multiple countries in multiple languages, tailored to the customer segments, industries, geographies, or business needs at the same moment.  

AI has the potential to create digital clones of your employees, it can spread fake news as easily as real news, it can be used for deception as easily as for benefit. Is your organisation prepared for the social, personal, cultural, and emotional impacts of AI? Do you know how AI will evolve in your organisation?  

When we focus on the future of AI, we often interview AI leaders, business leaders, futurists, and analysts. I haven’t seen enough focus on psychologists, sociologists, historians, academics, counselors, or even regulators! The Internet and social media changed the world more than we ever imagined – at this stage, it looks like these two were just a rehearsal for the real show – Artificial Intelligence. 

Lack of Government or Industry Regulation Means You Need to Self-Regulate 

These rapid developments – and the notable silence from governments, lawmakers, and regulators – make the requirement for an AI Ethics Policy for your organisation urgent! Even if you have one, it probably needs updating, as the scenarios that AI can operate within are growing and changing literally every day.  

• For example, your customer service team might want to create a virtual customer service agent from a real person. What is the policy on this? How will it impact the person? 
• Your marketing team might be using ChatGPT or Bard for content creation. Do you have a policy specifically for the creation and use of content using assets your business does not own?  
• What data is acceptable to be ingested by a public Large Language Model (LLM). Are are you governing data at creation and publishing to ensure these policies are met?  
• With the impending public launch of Microsoft’s Co-Pilot AI service, what data can be ingested by Co-Pilot? How are you governing the distribution of the insights that come out of that capability? 

If policies are not put in place, data tagged, staff trained, before using a tool such as Co-Pilot, your business will be likely to break some privacy or employment laws – on the very first day! 

What do the LLMs Say About AI Ethics Policies? 

So where do you go when looking for an AI Ethics policy? ChatGPT and Bard of course! I asked the two for a modern AI Ethics policy. 

You can read what they generated in the graphic below.

YourOrganisationNeedsanAIEthicsPolicyTODAY-1

YourOrganisationNeedsanAIEthicsPolicyTODAY-2

YourOrganisationNeedsanAIEthicsPolicyTODAY-3

I personally prefer the ChatGPT4 version as it is more prescriptive. At the same time, I would argue that MOST of the AI tools that your business has access to today don’t meet all of these principles. And while they are tools and the ethics should dictate the way the tools are used, with AI you cannot always separate the process and outcome from the tool.  

For example, a tool that is inherently designed to learn an employee’s character, style, or mannerisms cannot be unbiased if it is based on a biased opinion (and humans have biases!).  

LLMs take data, content, and insights created by others, and give it to their customers to reuse. Are you happy with your website being used as a tool to train a startup on the opportunities in the markets and customers you serve?  

By making content public, you acknowledge the risk of others using it. But at least they visited your website or app to consume it. Not anymore… 

A Policy is Useless if it Sits on a Shelf 

Your AI ethics policy needs to be more than a published document. It should be the beginning of a conversation across the entire organisation about the use of AI. Your employees need to be trained in the policy. It needs to be part of the culture of the business – particularly as low and no-code capabilities push these AI tools, practices, and capabilities into the hands of many of your employees.  

Nearly every business leader I interview mentions that their organisation is an “intelligent, data-led, business.” What is the role of AI in driving this intelligent business? If being data-driven and analytical is in the DNA of your organisation, soon AI will also be at the heart of your business. You might think you can delay your investments to get it right – but your competitors may be ahead of you.  

So, as you jump head-first into the AI pool, start to create, improve and/or socialise your AI Ethics Policy. It should guide your investments, protect your brand, empower your employees, and keep your business resilient and compliant with legacy and new legislation and regulations. 

The Financial Services industry can benefit greatly from leveraging Data and AI technologies to enhance client value and innovation. BFSI organisations want to deliver AI-driven outcomes.​

However, many AI projects fail to deliver long-term business value. Leaders in the industry must overcome challenges such as​

• Converting proofs of concept to scalable implementations ​
• Deploying end-to-end AI and Data strategies​
• Evolving business requirements​
• Responding to emerging trends such as Generative AI.

As a technology leader in BFSI, here are ​5 ways you can help deliver on your organisation’s AI ambitions.

1. Think in terms of outcomes – not use cases
2. Identify and eliminate digital debt
3. Build the right data platform architecture
4. Adopt a dual AI strategy
5. Be part of an innovation ecosystem

Read on to find out more.

5-Actions-to-Achieve-Your-AI-Ambitions-1

5-Actions-to-Achieve-Your-AI-Ambitions-2

5-Actions-to-Achieve-Your-AI-Ambitions-3

5-Actions-to-Achieve-Your-AI-Ambitions-4

5-Actions-to-Achieve-Your-AI-Ambitions-5

5-Actions-to-Achieve-Your-AI-Ambitions-6

5-Actions-to-Achieve-Your-AI-Ambitions-7

5-Actions-to-Achieve-Your-AI-Ambitions-8

5-Actions-to-Achieve-Your-AI-Ambitions-9

The global economy remains fragile due to multiple factors; and banking organisations will need to weather the storm. While large and well-capitalised banks are expected to fare better, there is a need for the industry to pursue new sources of value beyond traditional boundaries. ​

Banking industry leaders should be bold, proactive, and envision possibilities beyond current uncertainties. Technology has a key role to play in turning their innovation and resiliency goals into reality. ​

As organisations demand more industry-ready and localised services, global technology companies feel an active need to re-evaluate their capabilities and bridge gaps through partnerships and acquisitions. Ecosystm has been helping global technology companies evolve their partner strategies to remain relevant to the Asia Pacific market.

Our analysis of the tech acquisition landscape in Asia Pacific over the last three years shows that:

• While global tech providers are expanding their presence in Australia and Singapore, emerging markets in Southeast Asia are receiving a fair share of attention. 17% of tech acquisitions by global tech companies between 2020-22 have been in these markets.
• A quarter of the acquisitions were for product and platform capabilities. The rest were all done to bolster services portfolios – such as managed technology, business process, implementation & integration and consulting services.
• A large percentage of the acquisitions are to bolster industry capabilities through transformative technologies such as AI/ML, cloud and cybersecurity.

Here is the analysis of more than 100 acquisitions made by large global tech companies in Asia Pacific between 2020-2022.

Healthcare has transformed rapidly in the last few years – processes have become more agile; clinicians, administrative staff, and patients have changed their views on how healthcare can and should be delivered; and there is a greater reliance on technology today.

Despite challenges such as healthcare inequality and limited access to care for underserved populations, the future of Healthcare looks promising. 

We will see continued advancements in technology, increased collaboration between healthcare providers and patients, and a clear shift in focus on preventative care.

The Retail industry has faced significant challenges in recent times. Retailers have had to deliver digital experiences and delivery models; navigate global supply chain disruptions; accommodate the remote work needs of their employees; and keep up with rapidly changing customer expectations. To remain competitive, many retailers have made significant investments in technology. 

However, despite these investments, many retailers have struggled to create market differentiation. The need for innovation and constant evolution remains.

As retailers cope with hypersonalisation trends, supply chain vulnerabilities, and the rise of ESG consciousness, the industry is seeing several instances on innovation.