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AI MATURITY FOR SOLAR PV SMES

Project Sergio at the IS4SI Summit

13 September 2021 · Online, worldwide. Theoretical and Foundational Problems in Information Studies (TFP), a track of the IS4SI Summit 2021. · RESEARCH

deepkapha took a paper on AI maturity in solar photovoltaic SMEs to the IS4SI Summit in September 2021, and the whole engagement survives as an eighteen-minute recording.

Introduction slide listing solar energy complexity and SME constraints in adopting AI, set beside photographs of a coal stack at sunset and a solar array in a green field.

The paper is called Artificial Intelligence in the Energy Transition for Solar Photovoltaic Small and Medium-sized Enterprises. Four authors carry it: Malte Schmidt, Stefano Marrone, Dimitris Paraschakis and Tarry Singh, all credited to deepkapha.ai. Inside the lab it ran under a shorter name. The opening card says so in plain type beside the dk mark: Project Sergio, AI in Energy Transition. GreenScan, a climate AI startup, is credited as sponsor on the abstract card and again on the author card.

The venue was Theoretical and Foundational Problems in Information Studies, a track of the IS4SI Summit 2021. The summit ran online and worldwide from 12 to 19 September. Mark Burgin of UCLA chaired it, with an organising committee drawn from Vienna, Sofia, Sendai, Beijing and Gothenburg, and a programme committee spread across Bristol, Auckland, San Francisco, Madrid and Durham. Our slot is dated 13 September on the title slide.

The argument is narrow on purpose. Solar output is non-linear and weather-bound, which is exactly the kind of problem machine learning is good at. Small and medium operators are the ones with the least capacity to buy that capability. Existing AI maturity models, the Gartner five-level model among them, tell a company where it sits and then stop. The paper takes up what comes after the assessment: what a firm at Level 1, Awareness, actually does to reach Level 2, Active.

The method is design science research, split across three sub-questions and worked through a semi-structured literature review, semi-structured interviews, AI maturity assessments and expert evaluations. Every solar PV SME assessed landed in the first stage. The route out of it reduced to three dimensions: an AI strategy tied to the business the firm already has, simple data requirements starting with access, and people, meaning AI leadership and decisions pushed down rather than held at the top. Digital networking is what the paper puts forward as the cheapest bridge across an SME resource gap.

There is no photography from this one. The record is a single eighteen-minute screen recording, narrated over slides, running from a conference card and an author panel of four line-drawn portraits through to a wall of organiser logos and a closing thank-you. That is the entire archive for the engagement. The frames on this page are lifted from it.

FROM THE FIELD · 08 FRAMES
Slide headed Conceptualizing the Research, next to a five-level AI maturity model chart running from Awareness to Transformational, credited to Gartner 2019.
Slide headed Conceptualizing the Research, next to a five-level AI maturity model chart running from Awareness to Transformational, credited to Gartner 2019.
Problem and Objective slide setting out the main research question: what framework can help solar PV SMEs in their AI maturity stage transition.
Problem and Objective slide setting out the main research question: what framework can help solar PV SMEs in their AI maturity stage transition.
Research Design slide listing an interpretivist philosophy, a qualitative empirical design and a design science research strategy, with a three-phase DSR diagram.
Research Design slide listing an interpretivist philosophy, a qualitative empirical design and a design science research strategy, with a three-phase DSR diagram.
Findings for the first sub-question, with a red arrow dropped into Level 1 Awareness on the AI maturity model to mark where the assessed solar PV SMEs sit.
Findings for the first sub-question, with a red arrow dropped into Level 1 Awareness on the AI maturity model to mark where the assessed solar PV SMEs sit.
Findings for the second sub-question, naming AI strategy, data and people as the three dimensions for the step from stage one to stage two.
Findings for the second sub-question, naming AI strategy, data and people as the three dimensions for the step from stage one to stage two.
Significant Findings slide noting that AI immaturity in SMEs persists, that the resource shortfall is confirmed, and that AI leadership and digital networking can bridge it.
Significant Findings slide noting that AI immaturity in SMEs persists, that the resource shortfall is confirmed, and that AI leadership and digital networking can bridge it.
Conclusion slide summarising the answers to the three sub-questions and the guiding AI maturity stage transition framework.
Conclusion slide summarising the answers to the three sub-questions and the guiding AI maturity stage transition framework.
MATERIALS
Screen recording

sergio.mp4, 18 minutes 33 seconds, 1920 by 1032, HEVC with narrated audio. The only asset in the engagement folder.

Conference paperTO CONFIRM

Artificial Intelligence in the Energy Transition for Solar Photovoltaic Small and Medium-sized Enterprises. Schmidt, Marrone, Paraschakis, Singh. Not held in the folder.

WITH
IS4SI, International Society for the Study of InformationTheoretical and Foundational Problems in Information Studies (TFP), IS4SI Summit 2021GreenScan (sponsor)
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