How AI Could Transform Our Roles by 2028
The start of a new year is always a moment to pause, reflect, and envision. For me, it took nearly a month to regain the energy to write after the end-of-year break, oops!
But the pressure to look ahead feels more urgent than ever, especially with the rapid pace of technological advancements. The future seems closer now, as new advancements take shape and their effects start to ripple through our work and lives.
That’s why this first post of 2025 is dedicated to imagining how our professions in the development and humanitarian sectors could evolve over the next three years. Some changes are already underway, but we can expect them to become more mainstream and deeply integrated in the near future. My aim here is to simplify what could easily feel overwhelming, focusing on two key areas: office-based work and project implementation on the ground, as well as how these changes might impact different seniority levels.
Office-Based Work and Project Implementation
How our work looks like right now
At a high level, office-based work primarily revolves around performing repetitive and administrative tasks. Responding to emails, writing proposals, completing checklists for administrative processes, and coordinating approvals are everyday staples. These tasks often involve multiple back-and-forths between colleagues and external stakeholders, leading to delays and inefficiencies. Following up on administrative requests to ensure they don’t get stuck in the pipeline can also take up significant time and mental bandwidth. Overseeing project implementation involves coordination calls, with progress updates often relying on reports from field teams or partners, which may not always provide real-time data.
For project implementation, the work revolves around physically being on the ground: traveling from one venue to another, meeting partners, and ensuring that activities are implemented as planned. Teams spend time drafting requirements for activities and communicating updates or bottlenecks to office-based colleagues. There's a heavy reliance on manual troubleshooting and continuous follow-up with partners to ensure smooth delivery of project objectives.
How our work could look like in three years’ time
Possibility One:
Office-based work could become highly optimized through AI tools that seamlessly integrate with emails, calendars, and task management systems. Imagine an AI that tracks email conversations and suggests to-do lists based on deadlines, while also categorizing emails by priority and even drafting personalized replies in your tone. Proposal writing could be semi-automated, with AI generating drafts from historical data and pre-defined templates, reducing hours of manual effort. Similarly, checklists could be automatically generated and completed faster with AI integration.
Project implementation would benefit from AI-enhanced tools for planning and monitoring. Drafting requirements for activities would be a collaborative effort between AI systems and team members, with the former generating localized suggestions based on data. Vendor selection and contracting processes could be streamlined by AI, which can quickly analyze market options and provide recommendations. Additionally, predictive analytics could anticipate logistical or operational challenges before they arise, enabling proactive solutions rather than reactive responses.
Possibility Two:
AI tools could take over some routine tasks, allowing office-based staff to focus more on strategic thinking. For example, project coordination might no longer require frequent meetings or calls, as AI-powered dashboards could provide real-time updates on activity progress, bottlenecks, and risks. The AI could even recommend specific actions to address issues.
On the project implementation side, AR/VR (Augmented and Virtual Reality) technologies could enhance how field staff plan activities, conduct training, or engage with communities remotely, reducing the need for constant travel. For example, virtual site visits could allow staff to assess on-the-ground situations without leaving their desks.
Possibility Three:
AI might enable a shift toward more collaborative and interdisciplinary work. For example, office-based and field teams could work together on a single real-time platform that visualizes project timelines, resource allocations, and potential risks. AI could serve as a mediator, bridging communication gaps and ensuring everyone is on the same page.
Different Seniority Levels
How our work looks like right now
For junior staff, current tasks often include work like project research, data collection, entry, and drafting. Junior staff are also involved in operational tasks such as preparing logistics for activities, organizing events, and ensuring proper documentation. These tasks are time-intensive and repetitive but essential to the smooth running of projects.
For mid-level staff, the focus shifts toward project coordination, team management, and drafting/consolidating project proposals. These roles require balancing operational oversight with stakeholder communication, often under tight deadlines.
Senior staff typically engage in strategic-level responsibilities such as programme management, setting the vision and direction for key streams of work, fundraising, advocacy, and decision-making. These roles demand an ability to synthesize information, align priorities, and represent the organization externally.
How our work could look like in three years’ time
For Junior Staff:
AI will take over some of the repetitive aspects of their work, allowing junior staff to focus on higher-value tasks. For instance, instead of manually collecting and cleaning data, AI could handle these steps, enabling junior staff to focus on analyzing trends and making actionable recommendations. Drafting reports or logistics plans could also be aided by AI, enabling more precise outputs. This could increase the expectations placed on junior staff but also accelerate their learning curve and growth.
For Mid-Level Staff:
AI tools would reduce the burden of repetitive coordination tasks, such as following up with teams or consolidating project proposals. Instead, mid-level staff could focus on optimizing workflows, managing cross-functional teams, and addressing complex challenges that require human judgement. AI could provide personalized insights about team dynamics, helping managers create more effective and motivated teams.
For Senior Staff:
Senior staff could benefit from AI acting as a strategic advisor. AI systems could generate tailored reports highlighting key data points, trends, and options for decision-making. For example, while considering the launch of a new programme, AI could present several scenarios based on historical data and predictive models, enabling quicker, data-informed decisions. AI personal assistants could also streamline their schedules, prioritize tasks, and facilitate external communications.
The degree of implementation of these changes ultimately depends on the level of investment organizations are willing and able to allocate toward AI systems. However, it’s crucial to acknowledge that this investment goes beyond finances, it also involves fostering a culture of adaptability and innovation, as well as equipping teams with the skills to effectively leverage these tools. Data privacy and security must remain at the forefront of these transformations, as organizations will need to navigate the trade-off between affordability and solutions that ensure privacy, ownership, and ethical use of data.
Fortunately, as AI models continue to become exponentially more affordable and accessible, there is hope that public and non-profit organizations will also be able to integrate these systems and reap their benefits, not just large private entities. This democratization of AI could help level the playing field, enabling organizations of all types to optimize their workflows, enhance their impact, and focus on their core missions. The future of our professions will not simply be shaped by the tools at our disposal but by how thoughtfully and equitably we implement them to drive meaningful, human-centered change.
