Wealth management firms can unlock new insights and greater efficiency by embracing the power of automation and AI tools
The wealth management industry has undergone a significant transformation in recent years, driven by changing client expectations and powered by advancements in AI and automation. These technologies are not only streamlining operations but also enhancing client interactions and democratising financial advice, revolutionising the financial sector and an AI-enabled future for the financial services industry.
Wealth management firms are expected to fully embrace knowledge work automation platforms that enhance client information management and regulatory compliance by automating back-office processes such as document management and data analysis. This shift will enable wealth managers to focus more on high-touch client interactions and advisory strategy development, significantly reducing the manual workload that currently hinders service and productivity. By enhancing operational workflows, wealth management firms can offer clients more timely and personalised advice while improving cost efficiency across their operations. This means clients will receive better service and more tailored financial guidance, ultimately leading to improved financial outcomes.
One key area where automation will make a significant impact is document management. Wealth management involves handling a vast amount of content, from client records to compliance documents. Automating processes like document classification or regulatory compliance will reduce the time wealth managers spend on non-advisory work, allowing them to dedicate more time to fulfilling clients’ needs. Increasingly, these improvements show up right where advisors work. For example, relevant client information can be surfaced directly within Microsoft Outlook while an email is being drafted, helping advisors stay focused on the client conversation.
Data analysis is another critical aspect of wealth management that will benefit from automation. By leveraging AI-powered tools, wealth managers can analyse large datasets to identify trends, assess risks and make informed decisions. This capability will enable firms to provide clients with more tailored and timely advice, enhancing their overall experience and supporting compliance requirements.
Wealth management firms are also increasingly relying on AI to not just react to client needs but also predict them. By analysing past behaviours, market trends and financial goals, AI enables wealth managers to offer proactive advice on investment opportunities, portfolio adjustments and risk mitigation strategies. This predictive capability empowers advisors to anticipate market changes and advise clients on actions before those shifts occur. As a result, clients can make more informed decisions, potentially increasing their investment returns and enabling them to achieve their financial goals more effectively.
In addition, AI and automation are making wealth management services more accessible to a broader audience. Traditionally, personalised financial advice was reserved for high-net-worth individuals due to the high costs associated with human advisors. However, AI-driven platforms can provide personalised advice at a fraction of the cost, making these services available to a wider range of clients.
Self-service capabilities are another area where AI is making a significant impact. Clients can now access their financial information, perform transactions and receive advice through user-friendly digital platforms. This level of accessibility empowers clients to take control of their financial futures and make informed decisions without the need for constant advisor intervention. AI enhances client engagement and customer interactions, and supports embedded finance solutions that integrate financial services into digital ecosystems.
However, to see these benefits, firms must follow a careful, rigorous process when implementing AI and automation technologies. After the approval of the European Union’s AI act – which requires regular incident reporting and testing of ‘high-risk’ models – it is crucial for AI solutions to be provably safe and reliable.
This level of precision can only be achieved by building on a foundation of accurate and well-structured data. Companies should therefore start their AI journey by organising data across all of their operations, providing a reliable source of information for a generative AI tool to use. In doing so, they will be protecting their customers while also delivering vital work automation that will increase efficiency and streamline processes for employees.
As AI continues to evolve, it will play an increasingly important role in helping wealth management firms deliver superior service and achieve better financial outcomes for their clients. Embracing AI and automation is not just a trend but a necessity for firms looking to stay competitive in the rapidly changing financial landscape.
Beyond simple storage, a Document Management System (DMS) can actively manage documents through automation and intelligent features that improve consistency and reduce manual work.
How Workflow Automation Streamlines Document Processes
A Document Management System is more than a place to store files. It can actively manage your documents by automating workflows, reducing manual steps, and helping your team stay consistent and efficient.
This article explains how DMS workflow automation works and highlights key advanced features like version control, change tracking, approvals, and customization.
How does workflow automation within a DMS work?
Workflow automation in a DMS automatically routes documents through predefined steps like review, approval, and archiving. Instead of relying on email chains or manual handoffs, the system moves files to the right person at the right time.
For example, when someone uploads a contract, the DMS can notify the legal team, route it to a manager for approval, and then store the signed version with proper tags. The process is consistent every time and requires minimal oversight.
Automation also helps ensure compliance, prevent delays, and reduce human error by keeping work flowing smoothly and predictably.
Solutions like M-Files allow teams to configure these workflows visually, making it easier to adapt processes without custom development.
How do version control features in a DMS help prevent errors?
Version control in a DMS prevents errors by automatically tracking changes and keeping a full history of document edits. Users can see who made what changes and when, and if needed, roll back to a previous version.
This avoids problems like overwriting someone’s work, editing the wrong file, or sending outdated documents. Instead of guessing which file is current, teams work from one source of truth—clearly labeled, timestamped, and secure.
In platforms such as M-Files, version history is managed in the background, giving users confidence that no detail is ever lost.
Can I track document edits and changes using a DMS?
Yes, most DMS platforms include detailed change tracking. You can view document histories, compare versions, and audit who made each change.
This feature supports accountability, simplifies reviews, and provides a digital paper trail for compliance and quality assurance. Whether you are managing internal drafts or regulated documentation, edit tracking helps teams stay aligned and transparent.
Does a DMS support e-signatures and digital approvals?
Most modern DMS solutions support e-signatures and digital approvals. This allows users to sign or approve documents securely without printing or scanning.
Signatures are often timestamped, linked to the user’s credentials, and logged in the system for audit purposes. Approvals can be tied into automated workflows, triggering the next step in a process such as notifying a stakeholder, updating a file’s status, or archiving the document.
This speeds up processes like contract signoff, invoice approvals, and compliance documentation while reducing paper usage.
Some systems, including M-Files, support native e-signature tools and integrations with leading signature providers.
How does automated routing in a DMS enhance workflow efficiency?
Automated routing improves efficiency by eliminating manual steps in document handling. The system sends files to the next person or stage based on defined rules, such as document type, department, or status.
For example, a purchase request can automatically move from the employee to the manager to the finance team without anyone needing to email or assign the task manually. Alerts and reminders keep the process on track, reducing delays and bottlenecks.
This kind of automation helps businesses respond faster, reduce turnaround times, and standardize processes across teams.
Solutions like M-Files support these automations with rule-based routing and real-time notifications built into the platform.
Can I customize a DMS to match my organization’s workflow?
Yes, most DMS platforms offer workflow customization. You can design processes that reflect how your teams actually work, with custom steps, conditions, notifications, and document types.
This means you’re not forced to change your process to fit the tool—the tool adapts to your needs. Whether you’re managing employee onboarding, client contracts, compliance reviews, or design approvals, a customized workflow keeps everything consistent and trackable.
Customization also helps with adoption. When users see a system that mirrors their existing process but eliminates the busywork, they are more likely to use it.
M-Files enables customization through a low-code interface, allowing teams to build and adjust workflows without needing IT intervention.
Why workflow automation is a game-changer
Workflow automation is one of the most powerful capabilities of a modern DMS. It helps teams eliminate repetitive tasks, reduce errors, and move work forward faster. Combined with features like version control, edit tracking, digital approvals, and custom workflows, a DMS becomes more than storage; it becomes an engine for smarter, smoother operations.
If your current process is slow, manual, or inconsistent, these advanced features can create real value across departments and roles.
Tools like M-Files make it easier to embed automation into everyday document tasks, helping businesses work faster while maintaining structure and control.
Choosing between cloud and on-premises deployment is one of the first decisions when implementing a Document Management System (DMS). This guide explains the pros and cons of each model and answers common questions about security, scalability, and backup.
On-Premises vs Cloud DMS Deployment
One of the first decisions to make when selecting a Document Management System is how you want it deployed. Should your organization manage it on internal servers, or use a cloud-based platform maintained by the provider? Both models have their place, and each offers distinct advantages depending on your priorities.
This article explains the differences between cloud and on-premises DMS deployment, with answers to common questions about security, backup, and long-term scalability.
What is the difference between cloud and on-premises DMS?
The difference between cloud and on-premises DMS lies in hosting and management. On-premises systems are installed on your own servers and maintained by internal IT. Cloud systems are hosted by the vendor and accessed over the internet.
Cloud platforms offer easier deployment, lower maintenance, and better support for remote teams. On-premises models offer more control but require greater internal resources.
M-Files is available in both deployment models, allowing organizations to choose the option that aligns with their security, compliance, and infrastructure needs.
Are cloud-based DMS solutions secure?
Yes, cloud-based DMS platforms are secure when properly managed. They often include enterprise-grade encryption, secure transmission protocols, multi-factor authentication, and continuous monitoring.
Top vendors also maintain global infrastructure with built-in redundancy and hold certifications such as SOC 2 or ISO 27001. In many cases, the security standards of a cloud provider exceed what most businesses can maintain internally.
Cloud-first solutions like M-Files apply these protections by default, giving organizations a secure environment without the need for custom infrastructure.
How does a DMS address data backup and disaster recovery?
A cloud-based DMS typically includes built-in disaster recovery and automated backups. Your files are stored in multiple secure data centers, making recovery fast and reliable if disruptions occur.
With on-premises systems, backup and recovery are handled internally. You must create and manage your own policies, storage, and testing protocols to ensure business continuity.
Solutions like M-Files Cloud include redundancy and disaster recovery as part of the platform, easing the burden on internal IT teams.
How does cloud-based DMS scalability help a growing business?
Cloud-based DMS platforms scale easily as your business grows. You can quickly add users, expand storage, or activate features without infrastructure changes.
This flexibility supports fast-moving teams and remote work, one of the many advantages of a document management system. On-premises systems require physical upgrades and licensing changes, which add time and cost.
For organizations looking to grow without constant reconfiguration, platforms like M-Files offer rapid scalability and predictable performance.
Making the Right DMS Deployment Choice
Cloud and on-premises DMS solutions both offer value, but their differences matter. On-premises systems give you full control and deep customization. Cloud platforms reduce your IT burden, deploy faster, and scale with your business.
For many organizations, especially those prioritizing speed, flexibility, and simplicity, a cloud-based DMS offers a secure and practical path forward.
If you’re unsure which approach best fits your organization’s needs, our Ultimate Guide to Document Management Systems discusses cloud vs on-premises in context with other DMS decisions.
The pandemic drove numerous organizations to shift to remote work, a trend that is likely to persist. By adopting flexible work arrangements, companies can attract and retain top talent, boost employee satisfaction, and increase productivity. Hybrid work models, where employees divide their time between the office and remote locations, provide a balanced solution that accommodates diverse preferences and needs.
Digital Transformation
Digital transformation involves integrating new technologies across all facets of an organization, from operations to customer interactions. This integration boosts efficiency, security, and collaboration. For instance, AI and machine learning can automate routine tasks, freeing employees to focus on more strategic initiatives. Companies that successfully navigate digital transformation will be better positioned to respond to market changes and capitalize on new opportunities.
AI and Knowledge Work Automation
Artificial intelligence is set to revolutionize the workplace by empowering knowledge work automation. AI can manage tasks such as data analysis, customer service, and even creative processes, allowing knowledge workers to focus on high-value activities. This shift not only increases productivity but also improves job satisfaction by alleviating the burden of mundane tasks.
Enhanced Communication and Collaboration Tools
The rise of remote work has led to the creation of advanced communication and collaboration tools. Platforms like Miro and MURAL facilitate real-time collaboration, even when team members are in different time zones. These tools are essential for sustaining productivity and driving innovation in a distributed workforce.
Leadership and Adaptability
Successful leaders must be adaptable, adopting new technologies and work models to remain competitive. Organizations that embrace remote and hybrid work, invest in employee well-being, and prioritize continuous learning will thrive in the changing environment. Leaders who anticipate and respond to changes in the workplace will attract and retain top talent, driving long-term success.
Conclusion
The future of work is dynamic and ever-changing. Organizations that embrace digital transformation, leverage AI, and adopt flexible work models will be well-equipped to navigate the challenges and opportunities ahead. By fostering a culture of adaptability and continuous improvement, businesses can ensure they remain competitive and resilient in the face of ongoing technological advancements.
Accounting firms are facing new data security challenges from platforms like ChatGPT, Google Gemini, and Microsoft Copilot. Some knowledge workers are sharing client data with public GenAI platforms despite firm instruction. They use these platforms for a wide range of tasks such as accounting research, reviewing workpapers, client communications, and more.
Firms need to identify how to incorporate AI into their tech stack safely and securely. The best path forward is to provide their staff with firm-approved resources.
In this blog, we will explore how accountants can use Aino in their daily work with examples directly from the system.
Gain Time With AI-Powered Accounting
As someone that has previously worked in public accounting, I am familiar with juggling hundreds of documents across multiple clients and deadlines all within a couple of months. Reviewing these documents to familiarize myself with the client’s unique approach and understanding if this is even what I asked for was a regular occurrence. We were always looking for a better way!
Powered by M-Files generative artificial intelligence (AI) technology, Aino takes knowledge work to the next level by placing your firm’s information base at your fingertips. M-Files Aino organizes information, understands the context of documents, and allows users to interact with their content easily. Aino saves users time through automating necessary administrative tasks such as content summarization, accounting research, data entry and more!
Aino’s natural language model makes it simple for users to interact with their content and the platform.
The Natural Language Processing (NLP) Advantage
NLP techniques allow computers to understand human language. They bridge the gap between what humans speak and write and what computers can process. According to Gartner, “NLP provides intuitive forms of communication between humans and systems. NLP includes computational linguistic techniques (symbolic and subsymbolic) aimed at recognizing, parsing, interpreting, automatically tagging, translating, and generating (or summarizing) natural languages.”*
M-Files Aino is an example of how human users can interact with NLP technology. Aino has the capability to translate and generate text based on from partners to staff. Additionally, Aino can tag documents with metadata generated by Aino.
Aino Saves Time
According to the Work Trend Index Annual Report, 70% of people would delegate work to AI to lessen their workloads. Business leaders are twice as likely to say AI will provide value by boosting productivity versus cutting headcounts.
In the next section, we will focus on the following types of documents accountants frequently work on or receive from clients:
Engagement Letters/ Contracts
Leases
Client Provided Support
Confirming Completeness
When it comes to engagement letters and contracts, first accountants will identify if it is fully executed by the authorized signers. Secondly, they will ensure the time period and fees for covered services are stated correctly. Aino can quickly identify who signed your document and when. It can also identify the total cost for the engagement.
In the below example, we query Aino with three prompts. The provided answers will save us time reviewing each page manually.
Query: Who is the signor on this document?
Aino: Kyle Gillette
Query: When was this engagement letter executed?
Aino: 04/01/24
Query: How much do the services cost?
Aino: $50,000
To confirm this understanding, users can review the document either through the “preview” tab or opening the document. Users can verify that the Aino responses match the content of the document. Once they know what they are looking for, they can do this quickly.
Summarizing Content
Clients will often provide leases that are dozens of pages long. They may also be in a different language depending on the location of the leased item or asset. This increases the time the accountant needs to spend reviewing the document; to find the information they are looking for to support their findings.
With M-Files Aino, you can request a summary of the document in your language. This will allow accountants to understand if they have the correct documentation that aligns with their request. Secondly, they can ask Aino about rent cost, rent escalations, the lessor and lessee, and more. Once the accountant understands what they are looking for they can easily open the document and confirm Aino provided the correct information.
In the below example, we ask Aino more than one question at a time. Aino responds to each question accordingly.
Query: Who are the lessor and lessee in this lease?
Aino: Lessor: Real Estate Inc. Lessee: Acme
Query: How much does year 1 rent cost?
Aino: Year 1 rent cost: $60,000.00
Query: How much does rent increase annually between year 1 and year 2?
Aino: Rent increase annually between year 1 and year 2: $10,000.00
Query: Are there any other rent escalations in this lease?
Aino: There are other rent escalations in this lease, with the rent increasing by $10,000.00 annually.
Managing Client Provided Support
Clients provide data sets in various formats such as Microsoft Excel and PDF. To save accountants time formatting these documents, they can ask Aino specific questions about client schedules or listings. In the example below, we ask Aino to calculate the total expenses across multiple transactions.
Query: What are the total advertising expenses?
Aino: $125,000
Query: What period does this schedule cover?
Aino: For the year ended 12/31/23.
After reviewing the expense schedule, we can see that $125,000 out of $228,000 in total marketing expenses were attributed to advertising expenses for the period ended on 12/31/23.
FAQ
Q: Our firm manages a lot of sensitive information. How does M-Files Aino ensure the security and confidentiality of my client’s information?
A: Aino follows the security and access rights already established in your M-Files vault. Users will only be able to query or prompt documents they have access to. Unlike public GenAI platforms, information and queries stored in M-Files remain within the firm’s security environment overall reducing risk of security breach.
Q: M-Files Aino utilizes Natural Language Processing (NLP). Is there a learning curve for using this technology effectively?
M-Files Aino can be used right away as M-Files platform uses metadata and Optical character recognition (OCR) technology to understand the content in the document. The database from which Aino summarizes or provides information already exists in your vault. Due to M-Files‘ ability to maintain a single-source-of-truth and organize documents based on what they are not where they are stored, Aino can easily and quickly get to work assisting its users.
Courtney Kunzig, CPAIndustry Solutions Manager, AccountingM-Files
Courtney Kunzig, a seasoned accountant with diverse experience spanning various roles and industries, currently serves as the Industry Solutions Manager for Accounting at M-Files. Her expertise lies in leveraging technology to enhance employee experiences, streamline manual processes, and optimize time management within the accounting domain.
Kunzig explores the critical role of artificial intelligence and automation for accounting firms. The article delves into practical applications and strategies for reducing manual tasks and embarking on a digital transformation.
Kunzig discusses innovative strategies for addressing skills gaps in the accounting industry. She emphasizes the importance of retention and automation in nurturing talent and maintaining competitiveness.
Kunzig sheds light on the pivotal role of artificial intelligence in bolstering cybersecurity within accounting firms. Her article explores practical applications and proactive measures to safeguard sensitive data.
Courtney Kunzig’s thought leadership and contributions underscore her commitment to advancing the field of accounting through technology-driven solutions. Her expertise resonates with professionals seeking to optimize workflows, ensure compliance, and elevate client experiences.
The transformation power of technology is intertwined with efficiency and progress. Despite emerging challenges, automation offers practical efficiencies and benefits the life sciences sector are starting to consider in future growth planning and mapping workflow requirements
Knowledge work automation is at the heart of this digital transformation. It redefines how tasks are executed across various sectors. Work automation is essential for modern businesses, from streamlining routine processes to driving higher productivity.
The life sciences sector stands to benefit most from process automation. Life sciences encompasses biotechnology, pharmaceuticals, and healthcare. The sector has been significantly transformed by workflow and lab automation. More than 70% of life sciences organizations use automation for research and development processes.
This statistic illustrates how much life sciences organizations have embraced advanced data analytics and automation software development. For example, they are allocating significant resources to support each step of drug development.
The intersection of automation and life sciences is more than merely a technological meeting watermark. It represents a pivotal moment in pursuing innovations that can reshape the industry. This includes both drug discovery and medical research.
The Evolution of Knowledge Work Automation
The concept of automating business tasks has evolved. Changes started with the automation of labor during the Industrial Revolution. It continued with the advent of early computing systems.
Knowledge work automation has come a long way thanks to emerging technology. Breakthroughs in artificial intelligence (AI), machine learning, and computing power have propelled automation beyond routine tasks and manual work.
Advanced technologies have empowered systems to manage high-level decision-making, data analysis, and complex problem-solving. Large to small businesses use workflow automation, from manufacturing to financial services and healthcare, to work smarter. It’s not just about reducing mistakes. It’s about gaining a competitive edge.
Applications of Work Automation in Life Sciences
Applications that improve the efficiency of scientific processes in the real world include
High-throughput screening involves automated techniques that rapidly analyze large samples, allowing researchers to efficiently identify potential drug candidates and conduct robust experiments.
Data analysis and interpretation: AI automation can process vast datasets quickly and precisely. This helps scientists uncover meaningful insights and patterns.
Robotic process automation (RPA):RPAis increasingly crucial in life sciences R&D. Laboratory process automation leverages robotics to process and manage samples. It also streamlines repetitive tasks, increasing productivity and enhancing flexibility and agility. Benefits include reduced manual processes, heightened accuracy, standardized workflows, and cost savings.
Robotics in sample handling reduces the risk of human error and increases the throughput and accuracy of laboratory workflows.
Automated liquid handling systems perform precise and repetitive liquid transfers. This ensures accuracy in experiments requiring careful measurement and mixing. By automating these tasks, labs can achieve higher levels of consistency.
Benefits of Knowledge Work Automation
Information automation increases efficiency and will improve productivity. How? By relieving professionals of routine and time-consuming tasks. This allows researchers to spend more time on high-value activities. The quest to increase the speed of innovation and discovery is facilitated by knowledge work automation. It contributes not only to streamlined processes, but also to knowledge workers’ professional growth and effectiveness.
Knowledge work automation also drives enhanced data accuracy. Automated systems minimize the risk of human error, ensuring precision in analyzing data and interpretation. This improves the reliability of results and elevates the overall quality of R&D.
Advancements in information technology for life sciences include handling clinical trial data and improved document management for contract research organizations. These include streamlined workflows, enhanced collaboration, and reduced risks. This drives excellence in business operations and strengthens relationships with sponsors.
Integrating technology-driven solutions ensures advantages extend beyond efficiency gains. They positively impact the life sciences industry, from project management to regulatory compliance and enhance overall customer experiences.
Addressing Challenges with AI and Automation
What are some obstacles with the automation in life sciences laboratories?
Financial challenges hinder the adoption of process automation systems.
Long-standing obstacles in practices of academic research create resistance to future automation.
Despite expected progress in future design of affordable, lower-level automation equipment, the market still needs further development.
Meeting growing demand for environmentally conscious automation poses a challenge for developers.
Ensuring systems remain compatible with the innovative nature of researchers, preserving the freedom to create new protocols.
Life sciences researchers now need working knowledge in both traditional biology “wet lab” skills and emerging “dry” automation skills.
Spatial constraints within laboratories and cultural challenges contribute to knowledge gaps, leading to a lag in automation software
Trends in the Future of Automation
As automation continues to evolve, a higher elevation of tools and systems will emerge. They will be used to further enhance R&D efficiency and productivity. AI-powered drug design represents a significant trend in the future of work automation.
The long term shift towards AI promises to transform the identification of potential candidates. It will accelerate research timelines and enhance the precision of therapeutic interventions.
Another emerging trend is the seamless addition of decision automation in personalized medicine. Automation technologies are expected to be crucial in customizing medical treatments to individual patient traits. This trend encompasses the automation of processes related to patient data evaluation, treatment customization, and the efficient delivery of personalized healthcare solutions. The combination of automation and personalized medicine will optimize patient outcomes.
FAQ
How does knowledge work automation in life sciences differ from traditional office automation systems?
Unlike traditional office automation, knowledge work automation in life sciences is customized for complex tasks in biotechnology, pharmaceuticals, and healthcare. It involves advanced processes such as data analysis, decision-making, and problem-solving.
Why should life sciences embrace the automation of knowledge work?
Automating knowledge work management in life sciences streamlines processes and save time. This allows professionals to focus on high-value activities and contributes to maximized effectiveness. It also accelerates drug development, healthcare, and medical research innovations.
What makes the automation of knowledge work disruptive for life sciences?
The automation of knowledge work in life sciences disrupts traditional workflows by introducing advanced technologies such as AI. AI improves speed, accuracy, and overall effectiveness. This disruption transforms how tasks are executed, fostering breakthroughs in healthcare, drug discovery, and research.
FAQs is plural for more than one FAQ, because FAQ stands for Frequently Asked Questions. [MF1]
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