AI-enabled strategy training program
for executives, directors and managers
Assess yourself and your organisation
AI for business : how do you navigate the AI ​​era without being an accomplished multi-skilled technical architect or developer yourself?
Note : This survey can be carried out without submitting your contact details
You will obtain in real-time a pre-diagnosis according to 3 axes:​
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your level of AI-readiness at this stage,
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the maturity of your desire to leverage AI,
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the suitability of the following training program to your needs.
​This assessment does not prejudge the conclusions of a possible more complete analysis based on a direct interaction.
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My AI-readiness
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My motivation
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The alignment of my needs
What is an AI-enabled strategy ?
Observing hypergrowing organizations allows us to identify common success factors: strategic agility, exploiting the potential of AI (around 40% of new unicorns), creating and maintaining a competitive advantage through targeted investment in innovation. AI accelerates the analysis and evaluation times of high-impact decisions, provided that its tools and framework are chosen carefully.
An AI-powered strategy is dual:
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on the one hand, it identifies, qualifies and promotes a portfolio of projects exploiting the potential of AI, of all forms of AI;
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on the other hand, it benefits from the contribution of generative AI to carry out analyses, formalize and maintain a roadmap aligned with the underlying trends at work in the sector in question.
Its centrality in a dynamic ecosystem
A well-established group like a young shoot benefits from drawing inspiration from the examples given by unicorns. Each organization should have in its investment portfolio at least one "potential unicorn" line and one "AI-powered offer" line, otherwise it would leave the field open to competition in these areas. This is true in all sectors, industrial and service.
Let's take the example of the real estate sector in France and the United States. IAD (the initials mean "Real estate at home" in French) is disrupting the market in Western Europe by preempting the entire value chain of real estate agents, thanks to two key choices in its business model:
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leveraging AI to target the best matches between supply and demand, by maximizing the network effect;
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making its own agents benefit from it in the form of high-potential opportunities, by encouraging them to share their fees with their peers within the network
On the other side of the Atlantic, Zillow is also successfully disrupting the same market thanks to investments in AI, with similar levers. But instead of preempting the entire value chain, it remains confined to the upstream by generating leads. In this way, it feeds existing real estate agencies, stimulates their growth while limiting its own risks. The two models hold up. Each is adapted to its original ecosystem. It will be interesting to see which one will prevail globally in the future.
The two models hold up. Each is adapted to its original ecosystem. It will be interesting to see which one will prevail globally in the future.
IAD & Zillow : 2 AI-Enabled strategies disrupting the real-estate sector
REAL-ESTATE VALUE CHAIN
Supply-demand matching
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Prospecting and capturing mandates
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Property valuation
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Marketing & advertising
File instruction & administration
(Organising visits, Negotiations, Closing, Administrative & legal support)
AI LEVERS
IAD
ZILLOW
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Image editing & sorting
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Open data selection
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Automatic video-to-plan generation
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Listing optimisation
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Creation & optimisation of videos, photos & virtual tours
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Environmental data analysis
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Searching & matching
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Enriching property database
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Estimation, sponsored recommandations
OWN AGENTS
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Natural language search
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Personal recommendations
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High-precision estimations
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Home insights
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Showcase listings
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3D home tours
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Property database enrichment
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Market trend analysis
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Listing optimisation
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Fair housing classification
THIRD PARTY AGENCIES
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Voice to text
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Online training
Typical situations
Participants in this training typically face competitive challenges in a dynamic environment. The dynamism of this environment is measured, among other things, by the pace at which competitors introduce new offerings, the speed at which consumer practices evolve, the multiplicity of potential new business models, the impact of technology on the status quo, and the growth differential between new entrants and established players. Here are some examples of real-life situations from participants.
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the rise of coopetition in the pharmaceutical industry, the intensification of industrial transpositions of in-house processes to CDMOs (manufacturers, subcontractors), the generalization of systematic arbitration between internal production and outsourced production (make or buy), leading to profound changes at all levels: from a culture of top-down strategy to a logic of strategic agility fueled by state-of-the-art internal and external monitoring, from homogeneous skills in industrial production and BtoBtoC sales to a hybrid positioning in technical pre-sales, project management and BtoB commerce powered by AI, from rigid planning to end-to-end management of the value chain via a digital twin;
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the transition to AI-powered strategic project management in banking and insurance, by organizing the detection and financing of AI-powered initiatives at the front-office, middle-office and back-office levels, both internally and externally through strategic partnerships, using AI to augment the opportunity portfolio management processes;
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the introduction of AI-augmented design methods in the electronics industry, leveraging TRIZ ;TRIZ is an innovation method that consumes a large amount of data, which before the democratization of AI was difficult and risky to exploit without a great deal of mastery that few people had. AI is a game changer.
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the quest for the next pivot in a Biotech, suffering for too great a variety of products and services linked to a logic of pushed personnalisation, client by client ; how to identify the right direction, which offerings to decommission and why, which specialization to favor, which economic model to choose.
Cutting edge theory and practice
The tools and practices experienced by participants in groups, in an eminently interactive mode, are both tested in the field and based on a solid academic foundation.
Field experience in (extract):
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Pharmaceuticals
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Banking, insurance, capital markets
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Electronics & semiconductors
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Aerospace & Defense
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Digital services
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Real-estate
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Tourism & travel
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Professional services (consulting, accounting, coaching)
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Public services
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Non-profit
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Telecommunications
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Retail
Academic foundations (extract): experience is translated into practical tools, that are then matched with academic knowledge - papers published by professors and researchers from the following institutions (the theme in parentheses)
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Columbia University in NY (real options valuation)
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Stockholm University (hypergrowth factors)
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​ESSEC Business School (impactful hypergrowth)
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​​Stanford (hypergrowth factors)
Differentiating & innovative agendas
To each his or her own blue ocean. A so-called blue ocean strategy (named by W.C. Kim and R. Mauborgne - Insead & Harvard) is based on the awareness that a lot of knowledge (technological, organizational, economic, in human sciences) has not yet been transformed into concrete products or services. They constitute opportunities to differentiate oneself or even to innovate, with increased pricing power and a higher ROI than those of standard products or services. This underlying, lasting trend is directly linked to the democratization of access to increasingly rich and open data.
6 AI levers : an accelerator
Participants will discover 6 levers of AI, 6 levers specific to generative AI, 6 AI technologies, 6 tools powered by AI, 6 use cases of AI, 6 sustainable subtrends of AI (i.e. at least 6 key headings). It seems that in this training everything goes by 6.
AI-Enabled strategy training : proof by 6
AI sustainable trends
Surf on
AI use cases
Underpin
AI levers
GenAI specific levers
Implement
AI tools
Underpin
AI technologies
Theme # 1 : Designing and steering an AI-led agenda
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Investing in AI-powered solutions
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Planning and measuring AI lever performance - ROI
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Steering an AI portfolio
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Targeting high-potential functions, processes, assets, products and services
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The data question : reliability, availability, comprehensiveness, suitability, volumes
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Adapting an organisation for AI integration
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Management of appropriate skills and competences
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Change management in an AI era
Theme # 2 : Focus on a high-potential process
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Selecting a high-potential process
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The AI project sheet
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Candidate AI engines
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Target data sets
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Multiplying expertise through AI levers
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The AI machine-learning and deep-learning processes, seen from the business side
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Roles and responsibilities
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Managing the AI projects portfolio view
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Set-up and development of a specific GenAI - the roles of business leaders and functional experts
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Set-up and development of other types of AIs - the contributions of functional and business experts
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An introduction to AI architectures
Theme # 3 : Building and maintaining an AI strategy
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The decision process
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The embedded AI solutions (CRMs, ERPs, verticals, ...)
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Knowing and understanding AI trends - technological and market watch
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Knowing and understanding the various professions dealing with AI : current and new functions
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A training plan
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AI and agility convergence
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Planning product and service introduction with AI
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Valuation and arbitration of AI initiatives and outcome
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AI solutions : a landscape
Theme # 4 : Driving AI operations
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Producing and tuning business expectations for an AI-powered solution
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Interacting with the AI technical experts and management
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Detecting opportunities to leverage AI
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Selecting and sharing detailed use cases suitable to a specific function
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Qualifying an AI project's status and updating an AI project's portfolio
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Open innovation applied to AI : an accelerator
A flexible schedule
VS
Thematic sessions
Focus on in-depth exploration of each theme
Condensed sessions
Efficiently cover multiple themes
The choice of duration and distribution over time is open. There are typically 3 approaches:
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Each theme corresponds to a half-day.
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A selection of themes is condensed into one, 2 or 3 half-days, with an adapted pedagogy.
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All themes are condensed into one, 2 or 3 half-days.​
These half-days can be consecutive or spread over a few weeks.
A flexible venue
Sessions can be held either at your premises or at a third party location, at your convenience.
Optional follow-up sessions
T0
T0 + 1 month
T0 + 2 months
Training session
Coaching - tuning, continuous learning
Focus on key component
Field-testing
Field-testing
After the training, an optional W-shaped approach is recommended to take ownership of the shared tools and practices. The upper part of the W symbolises the preparation time (in a classroom, in coaching sessions, in an office with selected facilitators and leaders). The lower part deals with field testing, experimentation. Here is an example of a series of waypoints :​​
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Top-left of the W : training session, customisation of the approach to some specifics of the organisation, such as the matching between target indicators and indicators already available.
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First low-point of the W : field testing of a first tool or set of tools, such as "the strategic AI initiative hunter agent".
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Second high point of the W : stepping back and making corrections, such as tuning the evaluation method. Preparing for the application of the next tool.
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Second low-point of the W : new field testing.
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Top-Right of the W : stepping back and zooming in on a key element of an AI-Enabled strategy initiative, such as "Innovation portfolio management, TRIZ for services and AI".