#1 State-sponsored Attacks Will Alter the Nature Of Security Threats
It is becoming clearer that the post-Cold-War era is over, and we are transitioning to a multi-polar world. In this new age, malevolent governments will become increasingly emboldened to carry out cyber and physical attacks without the concern of sanction.
Unlike most malicious actors driven by profit today, state adversaries will be motivated to maximise disruption.
Rather than encrypting valuable data with ransomware, wiper malware will be deployed. State-sponsored attacks against critical infrastructure, such as transportation, energy, and undersea cables will be designed to inflict irreversible damage. The recent 23andme breachis an example of how ethnically directed attacks could be designed to sow fear and distrust. Additionally, even the threat of spyware and phishing will cause some activists, journalists, and politicians to self-censor.
#2 AI Legislation Breaches Will Occur, But Will Go Unpunished
With US President Biden’s recently published “Executive order on Safe, Secure and Trustworthy AI” and the European Union’s “AI Act” set for adoption by the European Parliament in mid-2024, codified and enforceable AI legislation is on the verge of becoming reality. However, oversight structures with powers to enforce the rules are currently not in place for either initiative and will take time to build out.
In 2024, the first instances of AI legislation violations will surface – potentially revealed by whistleblowers or significant public AI failures – but no legal action will be taken yet.
#3 AI Will Increase Net-New Carbon Emissions
In an age focused on reducing carbon and greenhouse gas emissions, AI is contributing to the opposite. Organisations often fail to track these emissions under the broader “Scope 3” category. Researchers at the University of Massachusetts, Amherst, found that training a single AI model can emit over 283T of carbon dioxide, equal to emissions from 62.6 gasoline-powered vehicles in a year.
Organisations rely on cloud providers for carbon emission reduction (Amazon targets net-zero by 2040, and Microsoft and Google aim for 2030, with the trajectory influencing global climate change); yet transparency on AI greenhouse gas emissions is limited. Diverse routes to net-zero will determine the level of greenhouse gas emissions.
Some argue that AI can help in better mapping a path to net-zero, but there is concern about whether the damage caused in the process will outweigh the benefits.
#4 ESG Will Transform into GSE to Become the Future of GRC
Previously viewed as a standalone concept, ESG will be increasingly recognised as integral to Governance, Risk, and Compliance (GRC) practices. The ‘E’ in ESG, representing environmental concerns, is becoming synonymous with compliance due to growing environmental regulations. The ‘S’, or social aspect, is merging with risk management, addressing contemporary issues such as ethical supply chains, workplace equity, and modern slavery, which traditional GRC models often overlook. Governance continues to be a crucial component.
The key to organisational adoption and transformation will be understanding that ESG is not an isolated function but is intricately linked with existing GRC capabilities.
This will present opportunities for GRC and Risk Management providers to adapt their current solutions, already deployed within organisations, to enhance ESG effectiveness. This strategy promises mutual benefits, improving compliance and risk management while simultaneously advancing ESG initiatives.
#5 Productivity Will Dominate Workforce Conversations
The skills discussions have shifted significantly over 2023. At the start of the year, HR leaders were still dealing with the ‘productivity conundrum’ – balancing employee flexibility and productivity in a hybrid work setting. There were also concerns about skills shortage, particularly in IT, as organisations prioritised tech-driven transformation and innovation.
Now, the focus is on assessing the pros and cons (mainly ROI) of providing employees with advanced productivity tools. For example, early studies on Microsoft Copilot showed that 70% of users experienced increased productivity. Discussions, including Narayana Murthy’s remarks on 70-hour work weeks, have re-ignited conversations about employee well-being and the impact of technology in enabling employees to achieve more in less time.
Against the backdrop of skills shortages and the need for better employee experience to retain talent, organisations are increasingly adopting/upgrading their productivity tools – starting with their Sales & Marketing functions.
Earlier in the year, Microsoft unveiled its vision for Copilot, a digital companion that aims to provide a unified user experience across Bing, Edge, Microsoft 365, and Windows. This vision includes a consistent user experience. The rollout began with Windows in September and expanded to Microsoft 365 Copilot for enterprise customers this month.
Many organisations across Asia Pacific will soon face the question on whether to invest in Microsoft 365 Copilot – despite its current limitations in supporting all regional languages. Copilot is currently supported in English (US, GB, AU, CA, IN), Japanese, and Chinese Simplified. Microsoft plans to support more languages such as Arabic, Chinese Traditional, Korean and Thai over the first half of 2024. There are still several languages used across Asia Pacific that will not be supported until at least the second half of 2024 or later.
Access to Microsoft 365 Copilot comes with certain prerequisites. Organisations need to have either a Microsoft 365 E3 or E5 license and an Azure Active Directory account. F3 licenses do not currently have access to 365 Copilot. For E3 license holders the cost per user for adding Copilot would nearly double – so it is a significant extra spend and will need to deliver measurable and tangible benefits and a strong business case. It is doubtful whether most organisations will be able to justify this extra spend.
However, Copilot has the potential to significantly enhance the productivity of knowledge workers, saving them many hours each week, with hundreds of use cases already emerging for different industries and user profiles. Microsoft is offering a plethora of information on how to best adopt, deploy, and use Copilot. The key focus when building a business case should revolve around how knowledge workers will use this extra time.
Maximising Copilot Integration: Steps to Drive Adoption and Enhance Productivity
Identifying use cases, building the business proposal, and securing funding for Copilot is only half the battle. Driving the change and ensuring all relevant employees use the new processes will be significantly harder. Consider how employees currently use their productivity tools compared to 15 years ago, with many still relying on the same features and capabilities in their Office suites as they did in earlier versions. In cases where new features were embraced, it typically occurred because knowledge workers didn’t have to make any additional efforts to incorporate them, such as the auto-type ahead functions in email or the seamless integration of Teams calls.
The ability of your organisation to seamlessly integrate Copilot into daily workflows, optimising productivity and efficiency while harnessing AI-generated data and insights for decision-making will be of paramount importance. It will be equally important to be watchful to mitigate potential risks associated with an over-reliance on AI without sufficient oversight.
Implementing Copilot will require some essential steps:
Training and onboarding. Provide comprehensive training to employees on how to use Copilot’s features within Microsoft 365 applications.
Integration into daily tasks. Encourage employees to use Copilot for drafting emails, documents, and generating meeting notes to familiarise them with its capabilities.
Customisation.Tailor Copilot’s settings and suggestions to align with company-specific needs and workflows.
Automation.Create bots, templates, integrations, and other automation functions for multiple use cases. For example, when users first log onto their PC, they could get a summary of missed emails, chats – without the need to request it.
Feedback loop.Implement a feedback mechanism to monitor how Copilot is used and to make adjustments based on user experiences.
Evaluating effectiveness.Gauge how Copilot’s features are enhancing productivity regularly and adjust usage strategies accordingly. Focus on the increased productivity – what knowledge workers now achieve with the time made available by Copilot.
Changing the behaviours of knowledge workers can be challenging – particularly for basic processes that they have been using for years or even decades. Knowledge of use cases and opportunities for Copilot will not just filter across the organisation. Implementing formal training and educational programs and backing them up with refresher courses is important to ensure compliance and productivity gains.