Turning AI Strategy into Enterprise Execution: Insights from Asia’s C-Suite Leaders

AI is moving quickly from boardroom ambition to operational reality. For organisations across Singapore and wider Asia, the question is clear: how can we create measurable business value while earning the trust of employees, customers, and the people responsible for managing risk?

This was the central theme discussed at Docusign’s private executive breakfast for Singapore Momentum. Hosted by Docusign’s CEO, Allan Thygesen, the breakfast featured a fireside conversation with Dr. David R. Hardoon, Accenture's Managing Director & Head of Advanced AI for Southeast Asia.

The discussion focused on practical guidance rather than hype, highlighting that AI success is not determined by technology alone - it depends on the connection between business strategy, operating models, governance, and people. Keep reading to discover more insights and perspectives on AI, straight from senior executives across Asia.

Start with the business outcome

Executives repeatedly brought the conversation back to business priorities: improving customer experience, reducing costs, accelerating revenue, increasing productivity, or reducing risk.

The question is not, “Where can we use AI?”, but rather, “What are we trying to achieve as a business, and where can AI help?” 

Agreements can be a practical place to begin, as they connect customers, employees, and partners with revenue, compliance, and risk. You can make informed, data-backed decisions when all of your agreements live on one trusted platform - a capability that is available with Docusign’s Intelligent Agreement Management (IAM) tool. IAM is an AI-powered platform that empowers you to connect and optimise every step of your business processes that involve agreements.

Measure value, not activity

The number of pilots launched, tools deployed, or employees given access to AI may show momentum, but none of these measures directly prove that AI is delivering value.

Leaders should define success before scaling a use case. Measures may include operating cost, customer response, productivity, risk or revenue velocity. 

Enable responsible progress through governance

Responsible AI does not mean waiting for zero risk. It means understanding the risks involved, putting appropriate controls in place, and making informed decisions about where AI can be used.

One useful test is to compare an AI-enabled process with the human-led process it would support or improve. In some cases, AI can maintain or reduce existing risk while improving speed and visibility.

Controls should vary by use case, with higher-stakes applications requiring more rigorous testing, oversight, monitoring, and escalation. If your organisation is looking to use AI to accelerate time to revenue and optimise agreement value - while still mitigating unnecessary risk - try Docusign Contract Lifecycle Management (CLM). 

Clarify accountability before scaling

AI initiatives often slow down because ownership is unclear, not because the technology is unavailable.

Before moving from experimentation to enterprise execution, leaders should be able to answer:

• Who owns the workflow and business outcome?

• Who monitors performance and manages risk?

• Who has authority to make final decisions?

Executive leadership has an important role in setting priorities, clarifying decision rights, and creating an operating model that enables progress within appropriate guardrails.

Don’t wait for perfect data

Executives cautioned that data is essential to AI, but waiting for perfect data can delay progress indefinitely. Business information is distributed across systems, documents, repositories, customer interactions, and teams. Its quality is rarely uniform.

A practical starting point is to understand where relevant information resides, who owns it, how reliable and accessible it is, and whether it is usable for a defined business objective. Organisations can improve data quality over time while progressing on priority use cases. 

For agreement-centric processes, this means connecting information across the agreement lifecycle so teams can act with greater context and confidence. Leverage the agreement data you already have into actionable business insights and opportunities with Docusign Agreement Manager.

Redesign workflows and prepare people for change

Perhaps the strongest message was that the biggest opportunity may not be automating a single task. It may be redesigning how work moves through the organisation.

AI can connect multiple stages of a process, from intake and validation through review, approval, execution, and follow-up. The goal is to reduce low-value manual work, improve consistency, accelerate outcomes, and give people more time for judgement and customer relationships.

The most valuable use cases can create benefits on both sides of the business: a faster customer experience alongside lower cost, less rework, better productivity, and improved process visibility. This transformation cannot be delegated entirely to technology teams. Leaders need to understand how AI changes day-to-day work, resolve tensions between control and business objectives, and help employees understand how their roles may evolve.

Thankfully, you can boost your productivity and speed with workflows that automate any agreement process, exactly the way that you want it, with Docusign Workflow Builder.

Ready to turn AI strategy into action?

The organisations most likely to make meaningful progress will treat AI as an enterprise change agenda, not a standalone technology program. Agreements are a natural starting point because making them more intelligent, efficient, and controlled can improve how work gets done while strengthening trust. 

If your organisation is ready to move from AI experimentation to measurable business impact, connect with Docusign today, and explore the value that IAM can bring to your business.