Future capacity building needs, constraints and a strategic model for empowering extension personnel as information managers

Introduction

Agricultural extension systems worldwide are undergoing a sustained digital transition in which extension personnel are expected to function not merely as technology disseminators but as active managers of information, drawing it from an expanding range of sources, processing it for local relevance, and pushing it out through an equally expanding range of channels (Roy et al., 2025) [2] . Realising this transition depends on whether capacity building programmes are designed around what extension personnel themselves say they need, rather than around a generic, one-size-fits-all training calendar, since a recent multi-state review of Krishi Vigyan Kendra personnel found that the lack of training opportunity, rather than infrastructure availability or cost, was the single largest constraint reported to ICT tool adoption (Singh et al., 2026) [1] , and a systematic review of climate-resilient extension services across Africa similarly identified interpreting data, using digital tools and systems-based reasoning as the specific competency gaps underlying weaker service delivery, ahead of the more commonly discussed problems of advisor-to-farmer ratios and funding alone (Nkhwashu et al., 2026) [3] . This need-based framing matters because digital competency among extension professionals in India remains, on the most recent standardised assessment available, only medium for close to half of those surveyed (Mukherjee et al., 2026) [4] , despite widespread awareness of digital tools, indicating that awareness and even access have outpaced structured, targeted skill-building. Evidence from a comparable Farm Science Centre training-needs study likewise found that assessed needs, rather than administrators' assumptions, produced sharply different priority rankings for subject matter, venue, duration, method and trainer preference among extension functionaries (Khan et al., 2023) [5] , reinforcing that capacity building planned without directly assessing personnel preferences risks investing training resources in areas or formats extension personnel are least likely to act on. A composite Information Management Index has already been reported for Tamil Nadu's extension cadre, together with item-level detail on the specific sources, processing methods and dissemination channels underlying it, but this body of work has so far described only present information management behaviour, leaving unanswered the forward-looking question of what future capacity building extension personnel themselves consider necessary, in which subject matter areas, through which venue, duration, method and trainer, and which specific constraints currently limit their information acquisition, processing and dissemination. Without this evidence, capacity building investment for this cadre risks being generic rather than targeted, and constraint-removal efforts risk being generic rather than stage-specific. The present study addresses this gap by assessing the future capacity building needs and the acquisition, processing and dissemination constraints of the same extension personnel population, and synthesising the results into a strategic model for empowering them as future "Information Managers".

Materials and Methods

The study was conducted in Coimbatore, Tiruppur and Erode districts of Tamil Nadu using an ex post facto research design (Singh, 1980) [6] during 2013-14, covering all blocks in the three districts. Of 154 extension personnel in position, comprising Agricultural/Horticultural Officers (AO/HO, n = 64), Assistant Directors of Agriculture/Horticulture (ADA/ADH, n = 33) and Deputy Directors of Agriculture/Horticulture (DDA/DDH, n = 24), 121 responded to a structured, pre-tested mailed questionnaire, the same sample and instrument previously used to construct this population's composite Information Management Index (Anand et al., 2014) [7] . Future capacity building needs were assessed across four preference dimensions, namely subject matter area (31 items), venue of training (14 options), method of training (35 options) and choice of trainer (8 options), each rated by respondents on a three-point continuum (most needed/preferred = 3, needed/preferred = 2, not needed/preferred = 1). A mean score (maximum attainable 3) was computed separately for the AO/HO, ADA/ADH and DDA/DDH cadres for every item, and the three cadre-wise mean scores were summed to obtain an aggregate score (maximum attainable 9) used to rank items overall; duration of training (6 options) was assessed as the percentage of respondents preferring each option and ranked accordingly. Constraints in information management were assessed separately for the three sequential components of the information management cycle, namely acquisition, processing and dissemination, using pre-tested constraint statements administered on a two-point (Yes/No) scale; the number and percentage of respondents reporting each constraint were computed and constraints within each component were ranked accord-ingly. Data for all dimensions were pooled across the AO/HO, ADA/ADH and DDA/DDH cadres and are presented descriptively as aggregate scores, percentages and ranks, consistent with the need-assessment and constraint-identification objective of this communication; no statistical significance testing was performed, and all data were collected with the respondents' informed consent.

Reliability and validity of the schedule

The mailed questionnaire comprised four parts covering profile characteristics, attitude towards ICT tools, information management patterns with constraints, and capacity building needs; all four parts, including the capacity-building and constraint sections used in the present study, were pre-tested on a non-sample group of extension personnel in an adjoining district and refined before administration. The psychometric soundness of the schedule is further supported by the independent validation carried out for the embedded ICT-attitude scale forming part of the same instrument: a split-half reliability coefficient of 0.698 (Spearman-Brown corrected, significant at one per cent probability) and a content validity index of 2.82 against a 2.5 acceptance threshold based on thirty subject-matter judges' ratings (Anand et al., 2014) [8] , both comfortably exceeding the minimum thresholds conventionally accepted for schedules comparing group means. Since the capacity-building and constraint items were drawn from the same pre-tested, expert-vetted instrument and administered to the same respondents under identical conditions, this independently validated reliability and validity of the co-administered attitude scale provides converging evidence for the soundness of the data reported here.

Results

Future capacity building needs in subject matter areas

Of the 31 subject matter areas rated (Table 1), digital documentation and presentation skills dominated the highest-ranked needs: MS Word (7.51), text document preparation (7.30), word processing in general (7.24) and MS PowerPoint (7.22) were the four most needed areas, followed by developing a script for radio talk (7.06), multimedia usage (6.76), the MS Excel package (6.64) and developing a script for TV talk (6.64). Composing mail through online mode (6.44) and transferring an idea into a popular article (6.60) completed the top ten. The lowest-ranked needs were preparing an Interactive Multimedia Compact Disc (IMCD) (4.17) and developing an audio cassette with field experience (4.10), the two most specialised and least routinely used skills among those assessed. Since these two aggregate scores are computed by summing three cadre-wise means (maximum attainable 9 per item, see Materials and Methods), the highest-need items (aggregate scores above 7.0, or a cadre-wise mean above 2.33 out of 3) represent needs that at least two of the three cadres independently rated close to "most needed", rather than needs driven disproportionately by any single cadre.

Preferred venue, duration, method and trainer for future training

Constraints in information acquisition, processing and dissemination

Constraints reported by extension personnel differed by stage of the information management cycle (Table 3). In information acquisition, non-availability of the latest scientific or popular journals in the office library (65.29%) was the leading constraint, followed by lack of ade-quate chance for attending trainings, seminars and workshops (57.02%) and limited guidance from higher officials (44.63%). In information processing, more time spent on miscellaneous work (73.55%) and inadequate time (71.07%) were the two leading constraints, well ahead of lack of updated information (52.07%). In information dissemination, inadequate funds (76.86%) and lack of conveyance facilities or mobile audio-visual units (69.42%) were the two leading constraints, followed by the large number of clients to be served (45.45%).

Discussion

The concentration of the highest capacity-building needs in MS Word, text and PowerPoint document preparation, ahead of more specialised digital skills such as multimedia usage or IMCD planning, indicates that a large share of this cadre's future training demand lies in consolidating routine digital documentation and presentation competency rather than in advanced or niche digital skills. This is consistent with recent evidence that digital competency among Indian extension professionals remains only medium for close to half of those assessed despite general awareness of digital tools (Mukherjee et al., 2026) [4] , suggesting that the present sample's own stated needs correctly identify basic-to-intermediate documentation skill, not exotic digital tools, as the priority training gap to close first.

The strong preference for short, three-to-five day, TNAU/KVK-anchored, lecture-with-AV-aids training, and for TNAU or KVK scientists as trainers rather than corporate or NGO resource persons, mirrors a broader Indian pattern in which extension functionaries' assessed training-needs priorities for subject matter, venue, duration, method and trainer diverge from what administrators typically assume, and points to the same practical implication: capacity building anchored in familiar public-sector institutions, delivered in short, AVaid-supported formats, is more likely to be attended and acted upon than longer or externally-sourced alternatives (Khan et al., 2023) [5] . It is also consistent with a wider systematic review finding that the specific competency gaps limiting extension service delivery lie in interpreting data and using digital tools rather than in advisor numbers or funding alone, reinforcing that skill- [3] . The constraint pattern observed here, dominated by non-availability of library resources and training opportunity in acquisition, time pressure in processing, and funds and mobility in dissemination, aligns closely with the finding that lack of training opportunity, ahead of infrastructure availability or cost, is the largest constraint reported to ICT-enabled extension work in a comparable cadre (Singh et al., 2026) [1] , and echoes an evolving view of extension as fundamentally an information-management function whose effectiveness depends on removing stage-specific bottlenecks across the full acquisition-processing-dissemination cycle rather than addressing any one stage in isolation (Roy et al., 2025) [2] . Notably, the leading constraint in each of the three components (library non-availability, miscellaneous workload, and inadequate funds) is largely outside the individual extension officer's control, indicating that institutional and administrative remedies, rather than officer-level skill deficits alone, are what training design must be paired with if capacity building gains are to translate into improved information management performance.

These findings are broadly consistent with a training-needs assessment of extension functionaries elsewhere in India, which similarly found that specific, locally-anchored institutional venues and structured need-based content, rather than generic training calendars, produced the highest reported training-need alignment among comparable functionaries (Khan et al., 2023) [5] , strengthening confidence that the present findings reflect a generalisable capacity-building pattern for public extension cadres rather than a purely local one. Taken together, the capacity building needs, preferences and constraints reported here support a strategic model (Figure 3

Future outlook: role of Artificial Intelligence in extension information management

The present findings also carry a forward-looking implication that extends beyond the 31 subject matter areas originally assessed: since data collection for this study, generative Artificial Intelligence (AI) and large language model (LLM)-based tools have emerged as a further, high-potential input to exactly the documentation, scripting and dissemination tasks that dominate the top of Table 1. A structured field study of 240 extension agents in Benin found that generative AI use was positively associated with improved advisory effectiveness, functioning as a decision-support aid that increased the speed, precision and relevance of the advice given, although agents' actual behavioural intention to adopt it remained more cautious than their attitudes toward it, reflecting professional accountability and trust con-cerns rather than technological resistance as such (Gouroubera et al., 2026) [9] . A bibliometric analysis of 337 Scopus-indexed studies on AI in agricultural extension published between 2010 and 2025 similarly concluded that hybrid systems, in which AI supplements rather than replaces human extension judgement, are likely to be the most successful future extension model, combining scalability with the inclusive, locally-adapted advisory relationship that farmers value (Saha et al., 2026) [10] . Closer to the present study's own setting, a recent technical evaluation of AI-based advisory tools piloted with roughly 800 farmers in Bihar, India and Kenya reported strong user satisfaction with LLM-based, voice-enabled advisory systems that integrate weather, soil and market data with curated agricultural knowledge bases, while also flagging language coverage and knowledgebase maintenance as continuing practical challenges (AIEP Initiative et al., 2026) [11] .

Read against the present results, these developments suggest two concrete extensions to the strategic model proposed here. First, several of the highest-ranked capacity-building needs identified in this study, including document and presentation preparation, radio-and TV-script writing, and popular-article writing, are precisely the tasks that generative AI tools can accelerate as a drafting aid without displacing the extension officer's own technical judgement and local knowledge; AIassisted document and content generation therefore merits inclusion as an emerging subject-matter area in future iterations of this needs assessment, delivered through the same TNAU/KVK-anchored, shortduration, lecture-cum-hands-on format already preferred by this cadre. Second, AI-based decision-support tools offer a direct, lowcost lever against the leading processing and dissemination constraints identified in Table 3, namely time pressure from miscellaneous workload and inadequate funds and mobility for reaching farmers, since AI-assisted drafting and translation can reduce the time cost of preparing information materials and voice-or chatbot-based dissemination can partially substitute for physically constrained outreach. These extensions are offered as a research and policy direction rather than as tested findings of the present study, and are consistent with the hybrid, AI-supplementing-rather-than-replacing-humanjudgement model that the wider literature currently recommends for extension services.

Conclusion

Assessing the future capacity building needs and constraints of 121 extension personnel in Tamil Nadu, using a schedule pre-tested for this population and independently supported by the split-half reliability and content validity established for its co-administered ICT-attitude scale, shows that the largest training demand lies in consolidating basic-to-intermediate digital documentation and presentation skills, best delivered through short, TNAU/KVK-anchored, lecturecum-AV-aid programmes led by familiar public-sector scientists, while the leading constraints across information acquisition, processing and dissemination are predominantly institutional (library access, training opportunity, time and funds) rather than skill-based. This distinction matters for policy because it indicates that capacity building investment alone, without parallel institutional remedies for the identified constraints, is unlikely to fully translate into stronger information management performance. The strategic model proposed here, linking capacity-building needs, format preferences and constraint removal to cadre-specific training design, offers extension administrators a practical, evidence-based basis for empowering extension personnel as future "Information Managers" for the benefit of the farming community, with the emerging role of AI-based decision-support and drafting tools identified as a concrete direction for extending this model as such tools mature. As a descriptive, single-population study, these findings are illustrative for Tamil Nadu's State Department of Agriculture cadre; replicating this need-and-constraint assessment across other States and departments, and empirically testing AI-assisted capacity building interventions against the priorities identified here, would help establish how generalisable and how actionable the present findings are elsewhere in India.

Acknowledgement

AcknowledgementThe authors thank the extension personnel of the Department of Agriculture and Department of Horticulture, Government of Tamil Nadu, in Coimbatore, Tiruppur and Erode districts, for their participation, and the Department of Agricultural Extension and Communication, Vanavarayar Institute of Agriculture, Pollachi, for institutional support.

References

1. Singh S, Doharey RK, Meena NR, Singh R, Singh A. Analysis and prioritization of constraints affecting ICT tools adoption among KVK personnel. Indian Journal of Extension Education. 2026;62(3):305-308.
2. Roy S, Mukherjee S, Yogesh BM, Singh G, Kalaiselvi P, Raj R, Balo S, Diwakar N. From field to future: the evolution of agricultural extension in the digital age for sustainable and revitalized rural economies. International Journal of Agriculture Extension and Social Development. 2025;8(11):530-540.
3. Nkhwashu F, Gcelu A, Sithole A, Sithole M, Tshwene C, Dagada M, Matiwane M, Olorunfemi O. A systematic review of knowledge, competency needs and constraints in climate resilient extension and rural advisory services in Africa. Discover Sustainability. 2026;6:Article 04275.
4. Mukherjee S, Padaria RN, Burman RR, Nikam VR, Velayudhan PK, Mahra GS, Aditya K, Chakrabarti B, Saini S, Shravani K, Ghosh B. Development and standardisation of a digital competency index for extension professionals of India: a principal component analysis approach. Agricultural Research. 2026;15(1):579586.
5. Khan S, Peer QJA, Kubrevi SS. Training needs assessment of extension functionaries for the training programmes conducted by SAMETI. Journal of Community Mobilization and Sustainable Development. 2023;18(2):657-663.
6. Singh S. Variable identification study vs. variable testing study: a methodological note. Indian Journal of Extension Education. 1980;16(1&2):1-4.
7. Anand K, Ravichandran V. Assessment of information management pattern among extension personnel. Trends in Biosciences. 2014;7(21):3402-3404.
8. Anand K, Ravichandran V. A scale to measure the attitude of extension personnel towards the Information and Communication Technology (ICT) tools. Trends in Biosciences. 2014;7(17):25832585.
9. Gouroubera MW, Segnon AC, Gouthon M, Moumouni-Moussa I, Zougmore RB. Generative AI use and advisory performance among agricultural extension agents in Benin. Frontiers in Artificial Intelligence. 2026;9:1763406.
10. Saha S, Patra A, Reddy MD, Prusty AK. Bibliometric analysis of the role of artificial intelligence in enhancing agricultural extension services. Indian Journal of Extension Education. 2026;62(3):27-34.
11. AIEP Initiative, Collis S, Kinyua F, Kumar V, Lakougna H, Merz C, Pandey K, Resch C. Building AI-based advisory services for smallholder farmers: technical learnings from the AIEP Initiative. arXiv. 2026;2601.11537.