Q&A with Mac Weaver, SVP and GM APAC, BlackLine, explores how organisations can build resilient, future-ready finance teams.
Why is there an imperative need for finance departments to adapt to technological advancements – particularly AI and Machine Learning – to drive organisational value?
Finance teams today manage large volumes of complex and often unstructured data yet many still rely on outdated systems that hinder agility and insight. AI and Machine Learning are essential to overcoming these limitations. These technologies automate manual tasks, improve data accuracy and enable faster access to insights that inform strategic decisions.
Predictive analytics for example can anticipate revenue patterns and cash flow shifts helping businesses stay ahead of change. AI also plays a vital role in risk management by detecting anomalies, identifying potential fraud and strengthening internal controls to ensure ongoing regulatory compliance.
Importantly AI enhances rather than replaces human judgement. By reducing time spent on repetitive processes finance professionals are free to focus on analysis, planning and guiding business strategy – with some enterprises reporting a productivity boost of 2.6 times. For instance, BlackLine’s solutions transform traditionally slow and inefficient processes by eliminating 50% of manual work and reducing close times by 70%.
Organisations that embrace AI-driven transformation are better equipped to respond quickly mitigate risk and generate long-term value. As business environments grow more dynamic finance functions must modernise to remain strategic partners in organisations in driving performance and resilience.
What does “data is the new currency” mean?
The phrase reflects the growing recognition that data has become a highly valued asset in today’s world – similar to the value of money in enabling transactions. Data holds immense value but only when used effectively.
In finance significant time is spent preparing and cleaning data before it can be analysed – delaying decision-making and reducing the ability to contribute strategically.
AI is transforming this landscape. By automating data preparation AI enables finance teams to extract insights with speed and accuracy shifting their focus from basic reporting to high-impact tasks like forecasting optimisation and risk mitigation.
However simply having access to data is not enough. Its value lies in its quality structure and relevance. Organisations that invest in clean reliable and well-integrated data are best positioned to unlock AI’s full potential. These companies can gain real-time visibility and insights making faster more confident decisions and remaining competitive in a rapidly evolving environment.
Data becomes a strategic asset when it drives smart decisions. To stay ahead finance teams must evolve alongside this data-driven shift combining technical capabilities with business acumen to deliver real impact.
How can companies achieve successful digital finance transformation and realise future-ready operations?
Digital finance transformation often fails when approached solely as a technology upgrade rather than a business-wide shift. One of the most overlooked success factors is strategic alignment. Without a clear vision and strong leadership across departments transformation efforts can lose momentum and deliver limited impact.
Equally important is change management. Employees may seek better systems but remain hesitant to adopt new tools without proper support. Clear communication leadership engagement and continuous training are critical to building confidence and long-term adoption.
Redesigning workflows before applying automation is also essential. Automating inefficient processes only magnifies existing problems. A future-ready finance function requires rethinking how work is done with AI and automation embedded to improve usability collaboration and results.
To succeed organisations must embed Digital Transformation into their culture. This means aligning technology leadership and people while partnering with experienced solution providers. When these elements work in unison finance teams can become more agile resilient and equipped to meet evolving demands.
What strategies do you think foster collaboration between CFOs CIOs and CTOs in driving digital initiatives?
Fostering collaboration between CFOs CIOs and CTOs is key for successful Digital Transformation and a primary strategy is building a shared vision to ensure digital investments deliver long-term business value. It’s important to address the common disconnect where financial transformation is often viewed as an IT initiative. A key challenge is the misalignment of priorities with CFOs often prioritising financial stability and ROI while CIOs and CTOs focus on technological scalability and innovation.
To overcome this a common vision should be built on mutual trust aligned objectives and transparent communication. This vision should be centered around the goal of autonomous finance – where AI-driven insights become integral to decision-making. When finance and IT work as strategic partners digital initiatives are more likely to be adopted and sustained.
A culture of collaboration with CFOs taking an active role in AI-led initiatives rather than delegating them to IT can help bridge competing priorities such as fiscal responsibility operational efficiency and technical agility. By working together these leaders can ensure AI and automation investments are relevant integrated and impactful driving greater agility and smarter decision-making across the organisation.
What measures can be implemented to upskill employees in AI literacy and data analysis to meet evolving industry demands?
To upskill employees effectively organisations must adopt a structured multi-pronged approach that goes beyond ad hoc training. First companies should develop role-specific learning pathways that embed AI and data literacy into employees’ daily responsibilities – especially within finance where real-time decision-making depends on data confidence.
Practical training programmes are key. These should include hands-on workshops simulation-based learning and tool-specific certifications that allow staff to apply new skills in familiar business scenarios directly. Learning must be continuous and scalable supported by internal learning platforms or partnerships with external providers.
Second businesses should foster cross-functional collaboration between finance IT and HR to identify evolving skill needs and track learning outcomes. This enables more targeted development and supports workforce planning.
Embedding AI-driven tools into regular workflows also accelerates adoption. Exposure breeds familiarity allowing teams to experiment learn and improve in real time.
Finally, organisations should recognise and reward digital capability-building. Whether through mentorship programmes internal knowledge-sharing or formal recognition reinforcing the value of upskilling helps embed a mindset of continuous improvement and ensures the workforce is prepared for a more data-driven future.
